Mobile Multimedia Information Retrievaldagda.shef.ac.uk/dispub/dissertations/2010-11/External/VSunder_Su… · Mobile Multimedia Information retrieval 2011 3 Contents Chapter 1: Introduction

Mobile Multimedia Information Retrieval

A study submitted in partial fulfilment

of the requirements for the degree of

Master of Science in Information Systems Management

at

THE UNIVERSITY OF SHEFFIELD

By

Vinod Sunder

September 2011

Mobile Multimedia Information retrieval 2011

1

Abstract

Background

This project reveals the variety of problems faced by mobile multimedia users and their

retrieval process carried out during the search for information on particular media types

(Video, Audio and Images) and the problems faced by them during the retrieval process.

Aims

The study carried out here aimed to understand the problems faced by mobile multimedia,

which are said to be one of the most happening fields in today‟s world.

Methods

Survey questions were developed, based on the variety of problems that are faced by the

mobile users in retrieval of information on particular media types and this survey is carried

out with 40 participants (Conducted between the age group of 20 - 27) using variety of

mobile devices and browsers. The response received is really interesting and the response

rate is 100%.

Results

The three key factors that are needed to be considered for Information Retrieval in Mobile

Multimedia devices are choosing multimedia mobile devices, choosing the best multimedia

web services, multimedia features widely used in mobile phones. Surveys played a crucial

role in determining these factors. There are also factors that affect users in handling

multimedia content in mobile phones. The three main solutions proposed to address the

problem of information retrieval are explained in detail in the implementation (Survey)

phase of the project.

Conclusion

We can conclude that the problems faced by the mobile users appear to be very less.

Operating systems and speed of the mobile Internet plays a vital role in retrieval of

information through mobile. Future work must be carried out with a detailed description of

each part of media types so that it will be more effective and pave a way for in depth

understanding of the problems faced by them.


2

Acknowledgements

It is a great indulgence to thank those who made this Dissertation possible such as my

parents and Friends especially Mr. Bhushan Sukumar and Mr. Shankar Arumugham who

gave me the virtuous support I required as my professor in helping me with the materials that

are required for my research.

I also would like to thank my Supervisor Prof. Nigel Ford, Whose encouragement, support

and guidance from the inchoate stage to the concluding stage helped me to complete this

project.

- Vinod Sunder


3

Contents

Chapter 1: Introduction

1.1 Aim……………………………………………………………………..9

1.2 Objectives.............................................................................................. 10

1.3 Motivation..............................................................................................10

1.4 Challenges..............................................................................................11

Chapter 2: Background

2.1 Information Retrieval.............................................................................12

2.2 Multimedia.............................................................................................13

2.3 Multimedia Information Retrieval.........................................................13

2.4 Search engines....................................................................................... 13

2.4.1 Working methodology.....................................................................14

2.4.2 Multimedia Search engines..............................................................15

2.4.2.1 AltaVista...................................................................................15

2.4.2.2 Yahoo Picture gallery............................................................... 16

2.4.2.3 Lycos search.............................................................................16

2.4.2.4 Google Image search................................................................16

2.4.2.5 Vast Video................................................................................17

2.4.3 Multimedia search Technology providers.......................................17

2.4.3.1 Alta Vista..................................................................................17

2.4.3.2 FAST (Fast search and Transfer) .............................................18

2.4.3.3 Inktomi......................................................................................18

2.4.3.4 Singingfish................................................................................18

Chapter 3: Design plan and timeliness....................................................... 19

Chapter 4: Literature review

4.1 Information Retrieval.............................................................................21

4.1.1 History of Information Retrieval......................................................22

4.1.2 User information needs and information retrieval...........................23

4.1.2.1Information behaviour.................................................................25

4.1.2.2 Information seeking behaviour...................................................25

4.1.2.3 Information searching behaviour............................................... 25

4.1.2.4 Information use behaviour......................................................... 26

4.2 Multimedia.............................................................................................26

4.2.1History of multimedia.......................................................................26

4.2.2 Features of multimedia.....................................................................28

4.2.2.1 Digital environment....................................................................28

4.2.2.2 Interactivity.................................................................................29

4.2.3 Factors affecting Multimedia............................................................29

4.3 Multimedia Information retrieval............................................................29

4.3.1 History of MIR...................................................................................31

4.3.1.1 Music retrieval............................................................................. 32

4.3.1.2 Image retrieval............................................................................. 33


4

4.3.1.3 Video retrieval.............................................................................34

4.3.1.4 Text retrieval............................................................................... 35

4.3.1.4.1 Text based application for Information retrieval.................. 35

4.3.2 Multimedia semantics...................................................................... 36

4.4 Mobile Multimedia Information retrieval.............................................. 36

4.4.1Wireless communications................................................................. 36

4.4.1.1 First generation networks............................................................37

4.4.1.2 Second generation networks....................................................... 38

4.4.1.3 Second and half generation networks......................................... 38

4.4.1.4 Third generation networks.......................................................... 38

4.4.1.5 Problems Faced by wireless multimedia.....................................39

4.2.2 User applications of mobile multimedia.......................................... 39

4.2.2.1 Introduction.................................................................................39

4.2.2.2 Experimenting with users............................................................40

4.2.2.3 Adopting commercial services....................................................40

4.2.2.4 Multimedia messaging service ...................................................41

4.4.2.5Enhanced messaging service .......................................................42

4.4.3 Mobile media .................................................................................. 42

4.4.3.1 Mobile Internet............................................................................42

4.4.3.2 Smart Phones...............................................................................43

4.4.3.3 Evolving Features........................................................................43

Chapter 5: Research Questions.................................................................. 44

Chapter6: Methodology

6.1 Survey....................................................................................................45

6.1.1 Survey Design..................................................................................45

6.1.1.1 Survey Definition........................................................................46

6.1.1.2 Generation of Questions..............................................................46

6.1.2Survey Implementation..................................................................... 47

6.1.2.1 Survey Monkey........................................................................... 47

6.1.2.2 Sampling for the Survey..............................................................48

6.1.2.3 Survey execution.........................................................................48

6.2 Ethics......................................................................................................49

Chapter 7: Results

7.1 Analysis of the survey...........................................................................50

7.1.1 Participants Background and Knowledge………………………… 50

7.1.2 Choosing Multimedia Mobile devices.............................................50

7.1.3Choosing the Best Multimedia web services....................................51

7.1.4 Multimedia Features Widely used in mobile phones.......................52

7.2 Problem identification and investigation...............................................53

7.2.1 Incompatible data Types..................................................................54

7.2.2 Consequences of using Multimedia Application in Mobile Phones 55


5

Chapter 8: Discussion

8.1 Solution discovery.................................................................................56

8.1.1 Enhance Primary Mobile Multimedia Operations...........................56

8.1.2 Mobile-Friendly Multimedia Website..............................................56

8.1.3 Unify Multimedia Data Types..........................................................57

8.2 Reflective Analysis...............................................................................57

8.3 Problems Encountered...........................................................................58

8.4 Evaluation..............................................................................................59

Chapter 9: Conclusions

9.1 Summary...............................................................................................61

9.2 Limitations............................................................................................61

9.3 Future directions................................................................................... 61

9.3.1 Human Centered Methods...............................................................62

9.3.2 Multimedia Collaboration................................................................63

9.3.3 No Solved Problems.........................................................................63

Chapter 10: References..............................................................................64

Chapter 11: Appendix

Appendix A ……………………………………………………………….74

Appendix B ………………………………………………………………..75

Appendix C……………………………………………………..…………76

Appendix D………………………………….…………………………….77

Appendix E……………………………………………………………...…80


6

List of Figures

Figure [2.1] Information Retrieval Process 12

Figure [2.1] Search engine working process 14

Figure [2.1] Variety of search engines 15

Figure [2.1] AltaVista search engine 15

Figure [2.1] Google Image search engine 17

Figure [3.1] Design Plan and Timelines 19

Figure [4.1] A simple information Retrieval Architecture 22

Figure [4.2] User Information Retrieval 24

Figure [4.3] Information Retrieval practices 25

Figure [4.4] Representation of Multimedia in Today‟s World 27

Figure [4.5] Features of Multimedia 28

Figure [4.6] Multimedia Information Retrieval and Management 30

Figure [4.7] Multimedia Information Retrieval Architecture 31

Figure [4.8] Multimedia- Image Information Retrieval and Management 33

Figure [4.9] Semantic Multimedia Database Architecture (SMDB) 36

Figure [4.10] Wireless Communications 37

Figure [4.11] Mobile Media 42

Figure [6.1] Methodology Process 45

Figure [6.2] Survey Implementation Process 47

Figure [6.3] Survey Monkey 48

Figure [7.1] Representation of Design feature rated highly by mobile users 51

Figure [7.2] Website used for Viewing and Watching / Images and Videos 52

Figure [7.3] Features Mostly used in Mobile Phones 53


7

Figure [7.4] Key problems faced in using Multimedia Content 53

Figure [7.5] Represents the least compatible data types 54

Figure [7.6] Factors affect when using Multimedia apps 55

Figure [8.1] Users Perspective on good mobile friendly web site 56


8

Abbreviations

EMS Enhanced Messaging Service

IR Information Retrieval

IS Information Systems

IRS Information Retrieval Systems

ISM Information Systems management

MDS Multimedia Database Systems

MI Multimedia Information

MIS MultiMedia Information Retrieval

MMS Multimedia Messaging Service

MoMIR Mobile MultiMedia Information Retrieval

SMDB Semantic Multimedia Database

SMS Short Message Service

WWW World Wide Web


9

Chapter: 1

Introduction

This MSc Individual project is based on Mobile Multimedia Information retrieval (MoMIR),

which is one of the emerging fields in information retrieval that involves searching or

querying of AV files, image files and graphical files (Canuel and Crichton, 2011). In the

recent years, the need for efficient searching mechanisms is greatly emphasised as there has

been a significant increase of multimedia content usage in the internet. A Multimedia

Information System (MIS) is an Information System (IS) that contains the metadata, features

and the multimedia content. The MIS is responsible for sharing of information to the users.

This takes into account the Type of information, its features and composition (Audio, video,

text, images), in order to allow the access to those information for the users (Premkamolnetr,

2002).

Generally, Users extract the information from IS in the form of queries. These queries are

translated and matched internally and are searched in the databases to find the information

requested in the query. Information retrieval (IR) includes the Logical aspects of describing

information and the specifications of the totality of the system. According to Keshavarz

(2008), Information systems are the way by which people and organisations, utilising

technologies, gather, process, store, use and disperse information.

Currently, the usage of multimedia information along with the growth of various

communication media has rocketed to a great level. This inevitably has generated new

problems at various levels of Information processing like Information flow, Storage and

Management (Vickery, 2002). Interestingly, the problems aroused revolve around the

extraction of information rather than the information itself.

1.1 Aim

The primary aim of this project is to analyse the impacts of multimedia content on mobile

technologies. In order to make an effective analysis, a comprehensive survey covering a

wide variety of mobile multimedia users must be taken. In this project, through the survey, I

intend to identify, analyse, comprehend and explain the problems faced by users at present.


10

1.2 Objectives

The primary objective of this project is to provide a comprehensive analysis of the problems

faced by MIR systems when dealing with multimedia content. This objective can be

achieved by executing a two-step methodology.

The first step would involve a deep understanding of MIR technology. In this report, as part

of solution discovery, the report affairs it with a variety of current and potential mechanisms

where information stored in the World Wide Web (WWW) could be organised, searched and

retrieved. As a result, a greater understanding of the problem is achieved.

The second stage of the process would include a detailed study of search behaviour on the

mobile platform by analysing the web search developed in recent years. This is achieved by

conducting a survey report and the inference gained from the report would greatly help in

analysing the problems faced by users regarding MIR.

Nowadays, a general belief is that, Multimedia Database Systems (MDS) provide content-

based retrieval facilities, which facilitates query that refers to several data types

instantaneously. There are strategies related to finding documents in a MDS, which provide

additional information concerning user needs and behaviour. This could help in discovering

more potential solutions to certain problems found in web.

1.3 Motivation

In recent years, there has been a significant development in MIR systems. Due to this

unprecedented growth of multimedia services, high volumes of data are used in wireless

communications & future generation systems.

The growth and development of mobile computing devices, composed with high speed,

reasonable mobile networks, have contributed a lot to mobile multimedia by increasing their

intricacy and variety of applications and facilities provided to the end-users. Furthermore

there is a great revolution in this field with the innovative developments in the novelty, types,

number and difficulty of the applications used in mobile multimedia and their facilities.

Due to the evolving business environment nature and high expectations, satisfying the user‟s

requirements is a big task. User satisfaction involves quality, reliability, service & cost. In

this project we are going to analyse deeply on the problems that are faced by the mobile

users during the retrieval of multimedia information. Moreover Mobile Multimedia is one of


11

the interesting research topics that provide great opportunity for researchers to analyze and

find an effective solution to these problems.

The two main fundamental necessities of multimedia information retrieval systems are:

1. Searching for a particular type of media item: There are few limitations in

the current systems such as understanding the user‟s information needs

2. Ways in which the search process is carried out

1.4 Challenges

Due to rapid advancement in web and mobile technologies, the exposure experienced by

users varies greatly. One of the primary challenges in this project would be standardize the

requirements of the users in the survey. Obtaining a clear feedback from the participants

would also be challenge due to different mobile devices and technologies used by the users.

Understanding this feedback and using it in this report would also post a challenge. An

intense research on MIR systems and its influence on current technologies will be a

challenge throughout the project. In order to understand the cons of today‟s MIR, one has to

have a clear understanding of the working process of it. This would depend greatly on the

quality of research and could possibly be more time consuming.


12

Chapter: 2

Background

The background information plays a vital role in the dissertation, which highlights the

pragmatic groundwork of the chosen topic. The main purpose of the background section is to

give the reader an insight of the background concepts and models that are used for this

project.

In this section I have given a detailed overview of Information Retrieval, Multimedia,

Multimedia Information Retrieval and the search engines associated with it to retrieve the

multimedia information.

2.1 Information retrieval

Information retrieval is the process of finding the documents of an unstructured description

that satisfies an information need from huge collection of databases. They are also called as

information storage and retrieval (Manning et al, 2009). According to Ruthven (2008), IR is

the ability and science of retrieving information from a group of documents that serve the

needs of the user. IR concerns about the representation of information, storage and access to

those information.

Figure 2.1: Information Retrieval Process

Source: Magalhaes, 2008


13

Figure [2.1], represents the information retrieval process. According to the process defined

by Magalhaes (2008), a query is given from the user and the information related to those

query are matched and retrieved from the information database and the document is then

presented to the user. For e.g.: A query is searched with the name Sheffield from the user,

the information relating to those queries are searched in the information database and the

retrieved information related to those queries are translated into user-friendly format and

presented to the user.

2.2 Multimedia

In the past, there was an assumption by some people, that Multimedia information content

represents Multimedia Entertainment Industry. During those days, the difference between

Multimedia industry and multimedia information was unclear. According to Attamah and

Robert (2010), Multimedia can be defined as the mixture of graphics, sound, animation and

video translated in a digital format.

But today, there is a clearer view on Multimedia information content and it can be generally

defined as the combination of text, data and images of all categories and sounds within

single, digital surroundings (Cloete, 2009).

2.3 Multimedia information retrieval

MIR can be described as a process involved during the search of media types like Audio,

Video & Graphic. According to (Vakkari and Jarvelin, 2005), MIR is one of the vast

research-intensive fields, where a wide range of data types are open for researchers and

analysts for study. These data types include text, hypertext, audio, graphics, animation,

image, video, rich text, spread sheet, presentation slide etc.

2.4 Search Engines

Search engines are web services that are used to extract information from all over the web,

organise and reproduce them in desired format of the user (Carpineto et al, 2009).

Traditionally, search engines concentrated on text materials, i.e. web pages. In this section, I

have briefly described on different search engines and their various techniques implemented

for searching.


14

2.4.1 Working Methodology

According to Sonera media lab (2002), Search engine consists of three main components:

1. Spider - Also known as a crawler or robot and it is the heart of the web search engine. It

is an independent web client that makes connections to the web server automatically.

2. Parser or Indexer - words in the form of textual objects are saved in the index along

with the information‟s related to the word locator.

3. Query Engine - checks with the index search and it provides the answer related to those

queries. In general, users won‟t interact with the query engine; instead the queries are

made via web interface. The query typed in the web interface takes it directly to the query

engine and the reply is sent in the suitable format that is understood by the user.

Figure 2.2: Search Engine working Process

Source: Sonera Media Lab, 2002 (Online)


15

2.4.2 Multimedia Search Engines

There are varieties of search engines used to retrieve the information, but few search engines

are really effective for the retrieval of particular media types. Let us discuss some of the

major multimedia search engines that will be helpful for user to retrieve their information

easily in various aspects. Figure [2.3] gives an overview of some of the existing search

engines available for the users.

Figure 2.3: Variety of Search Engines

Source: Peak Positions, 2011 (Online)

2.4.2.1 Alta vista

It is developed from AltaVista‟s crawler technology. It is same as AllTheWeb.com (At

present it is redirected to yahoo search) where images, audio, video can be accessed easily.

Some of the speciality in this is types of image collection, such as Getty images (can be

licensed professionally), Corbis and CDNOW (Notess, 2000).

Figure 2.4: AltaVista Search Engine

Source: http://www.altavista.com/, 2011 (Online)

http://www.altavista.com/


16

In addition to this general web Crawl, Alta vista allows access from their sites associated

with it. For the video search their main associated partners includes, ABC News, Launch.

Com, Vidnet and Merrill Lynch. For the MP3/Audio their partners include Riff age and e-

Music.

2.4.2.2 Yahoo! Picture gallery

(http://images.search.yahoo.com/)

It is one of the biggest picture galleries where nearly 400,000 pictures are available and they

are organized into various categories and can be accessed by the keywords in the title (see

Appendix A).

2.4.2.3 Lycos search

(http://www.lycos.com/)

Lycos (see Appendix B) uses FAST‟s technology for searching the MP3 files. It is one of the

fast multimedia search engines, where the search is based on the image, video and audio

sounds, which can be accessed fast. It is well known by comparing the MP3 results with

their technology provider AllTheWeb. Com (Sullivan, 2003).

But for getting access to the Music files, there is a separate search carried out at the Lycos

music (http://music.lycos.com), which has a MP3 search engine and can find many audio

files in the MP3 format.

2.4.2.4 Google image Search

This is one of the biggest image searches, which contains information from more that 250

million web images. All the text that is entered in the search engine can be directed

immediately to the Google search. Additional features include restriction of images

according to their sizes, file types and colour.

http://images.search.yahoo.com/

http://www.lycos.com/

http://music.lycos.com/


17

Figure [2.5], shows Google Images search engine along with the homepage of Google

images. Here, I have attempted to search with the keyword London and there are plenty of

images available for that search, likewise we can search with the image size, colour and file

types.

Figure 2.5: Google Images Search Engine

Source: http://www.google.com/imghp, 2011 (Online)

2.4.2.5 Vast Video

(http://www.vastvideo.com/)

It is one of the biggest video search web sites that allow searching of nearly 18,000 video

clips in windows media format. These videos are subdivided into 13 categories, so it is easy

to find the video clip by searching into those categories. It is also feasible to buy the video

types that are found.

2.4.3 Multimedia search technology providers

2.4.3.1 Alta vista

(http://www.altavistaservices.com/)

Provides Multimedia search as an elective package for its internet search service

http://www.google.com/imghp

http://www.vastvideo.com/

http://www.altavistaservices.com/


18

2.4.3.2 FAST (Fast search and transfer)

(http://www.fasttechnology.com/)

It is based on the same core technology used in AllTheWeb. Com search engine, it uses same

index for their queries.

2.4.3.3 Inktomi

(http://www.inktomi.com)

Provides media search as a supplementary service for its normal type of searching text, at

present Inktomi uses Singingfish‟s content for its media search, so it is easily accessible to

search the same type of media formats with the Singingfish Multimedia search.

2.4.3.4 Singingfish

(http://singing-fish.com/)

It is a subsidiary of Thomson multimedia, developed for searching multimedia files, one of

the specialities to be noticed here is Singingfish has retrieved and indexed over 18 million

streams and media files. Some of the notable things here in this database contain links that

can be accessed to Microsoft windows media formats, apple quick time, MP3 etc…

Conclusion

Service providers like FAST has the largest media file; on the other hand Alta Vista has the

most expensive query language. Singingfish Multimedia Search and Inktomi Media search

do not contain image files, thus their indices are comparatively smaller. According to

International telecommunications union (2007), nearly 87% of web users use search engines

or related search tool to retrieve information. To conclude with there are varieties of search

engines that provide easy access to the users, the multimedia field is very huge and retrieving

the exact information for users depends on the query they give.

http://www.fasttechnology.com/

http://www.inktomi.com/

http://singing-fish.com/


19

Chapter: 3

Design Plan and Timelines

The project proposal was finalised and commenced in June. I have split the entire project

into phases namely Project Preparation, Designing Methodology, Designing Survey &

Dissertation as shown in Fig [3.1].

Project Preparation

This phase was carried out for 13 days where basic concepts involved in the project like

Information technologies, Multimedia concept and the problems faced in today‟s multimedia

was understood. This is a crucial phase as I need to have an in-depth understanding of the

concepts involved in order to be in a position to discover solutions to the problems identified

as the project progresses. The background research carried out for Mobile Multimedia and

Information Retrieval help me gain a good understanding of the current multimedia industry.

Figure 3.1: Design Plan and Timelines


20

Designing Methodology

In this phase, the methodology or process flow that is going to be implemented in this project

is designed. In this phase, I had initially planned to have one-on-one sessions with users in

order to discuss the current trends and difficulties faced by them in handling multimedia

content. As this process was more time consuming and had more constraints involved, I had

to use surveys to collect data from the users. With the survey answers the problems are

identified and the responses for the questions are collected, which paved way in writing the

methodology by analyzing the problems, where a clear idea of suggesting the solutions for

problems are given.

Dissertation

This is last and the core phase of the project. In this phase, the execution of the survey is

done and the entire process is documented. The problems faced by the users in handling

multimedia content using their mobile devices are identified. An analysis of the survey is

done and scope for solution discovery is identified. The possible solutions to the problems

faced by present user‟s is proposed, explained and documented. A reflective analysis made

on the project and a conclusive result is summarised.


21

Chapter: 4

Literature Review

In this section I have listed an in-depth evaluation of previous research that was carried out

in the field of Information Retrieval and Mobile Multimedia Information Retrieval. In

addition to the evaluation, I have also given a detailed overview of the various concepts in

Mobile Multimedia and the information retrieval process associated with it.

4.1 Information Retrieval

Information processing and Information Systems management (ISM) came into existence

several decades ago. The earlier systems in the 90s supported text based documents only and

the other types of data were discarded or left unprocessed in the IR systems. According to

(Marchionini and Komlodi, 1998), some processes followed by the IR systems in

information retrieval and processing are still the same. These processes can be referred to as

modules as given below.

1. Analysis Module – This extricates vocabulary from documents.

2. Indexing Module – This accesses document efficiently through its information

symbols.

3. Query Processing Module – Transforms the information needs of user into

information symbols (could be machine dependent).

4. Retrieval Module – Ranks documents that are stored based on the resemblance

between information symbols.

In the year 1990, most of the people wished to get their information from other people who

have knowledge about the relevant topic, rather than using IR systems (Belkin, 1980). The

rapid growth of web search engines in the recent years has helped people in retrieving

information quickly and effectively. In the future, web searches are expected to improve

even more and are on track to become a standard or a common mean for finding information.

According to Fallows (2004), “92% of Internet users say the Internet is a good place to go

for getting everyday information”.


22

With the explosive growth of computers and internet, the use in amount of information

available has been increased with an astonishing speed and people have wide access to those

information. Taking all these into consideration Dimmick et al (2004) says that the

development in the establishment of recent electronic systems has a great impact on the way

in which people can search and retrieve information.

There were some challenges faced when providing the exact information access to a given

query evolved to give an ethical approach to search a various forms of information content.

Initially, IR systems began with scientific publications and public records. This was also the

main area of research for some time. But eventually, the process spread to other professional

areas like Medicine, Journalism and Law.

4.1.1 History of Information Retrieval

“Information retrieval embraces the intellectual aspects of the description of information and

its specification for search, and also whatever systems, techniques, or machines are

employed to carry out the operation” (Mooers, 1951).

Figure 4.1: A Simple Information Retrieval Architecture

Source: I.R.I.S Working Group, 2011 (Online)


23

The figure [4.1], shown above defines the various presentations of queries and its replies are

interchanged between the clients and the servers in a dispersed multimedia search and

retrieval systems. In this process, the query is given to the responder from the requester and

the query is partitioned and searched through each document database. The result of the

search is carried out to the requester. For e.g.: If the requester gives a query with the name

Sheffield University, then the query is split up and searched with the names Sheffield and

University and the information related to those queries are filtered and turned out to the

requester.

The research methods implemented for IR research varied greatly with time. In the early

1980s, Classic System Oriented approach was used and was followed by Cognitive User

Oriented approach. In the recent years, user interest has changed and direct interaction with

the system is implemented.

This allows them to have a clear view on the information and their knowledge is raised

resulting in the user and document modelling techniques. These techniques follow the nature

of the documents that are searched by the users. The Human machine interaction (HMI)

takes the new path and it is called human-machine human interaction (HMH) (David and

Maghrebi, 2007).

According to (Hawkins, 1983), the retrieval methods used in IR Systems relies heavily on

user modelling and on the requirements translated from user needs and his hierarchical

knowledge. In reality, a general user is not expected to deliver his needs efficiently and to

translate them into machine-dependent queries. As a result of this ineffective system, an

external approach is implemented, where researchers are requested to carry an effective and

detailed study of the user and the environment in which he is consistently exposed.

According to (Wilson, 1999), the problems and deficiencies related to IR systems are

connected to the organization; the way we present our information and the way we define

our tasks. Author (Salton and McGill, 1983), believes that the real problems raised in the

information retrieval process doesn‟t correspond to the informational objects adequately.

4.1.2 Users Information needs and Information retrieval

The rapid growth of multimedia information and the developments made in variety of

communication media has created new problems at different levels, which includes the

frequency in the flow of information, problems in data storage and management. These

difficulties have restricted the access to existing information. The primary goal of this


24

approach is the users. The main purpose of IR is to meet user‟s information needs. Some

different descriptions of the concept of information retrieval are given below

Author (Kraft and Bookstein, 1978),

explains that „the necessity to fill up a

noted deficiency in information, for

example a defect, a vacuum or a gap is

defined as information needs. This notion

of information need also relates with the

concept of relevance, which is an example

for the concepts related to information

retrieval. Figure 4.2: User Information Retrieval

According to (Kelly and Fu, 2007), to meet the information needs, information retrieval is

undertaken, because of this the concept of information in the information retrieval field is of

great importance. It is by several queries that the user expresses his information needs .The

first difficulty for the user is found in this stage in the information system operation.

The user expresses precisely about information needs in the form of knowledge of his

research domain, this is the reason why the information needs are translated into the system

language, and this theory was explained by (Beaulieu, 2003).Various thought provoking

schools have emerged in an attempt to meet the information needs of users.

To clarify the information requirements depends on the level of user‟s domain knowledge in

which he makes his research and also on the information system knowledge, it is on this

basis of knowledge that the user‟s capacity is depended. The various ways of approach has

been drafted from „Information Access and Information Needs‟ by Kuhlthau (1991) and

„Information practise‟ of Wilson (1999).

Based on Kuhlthau‟s model, the information retrieval process is divided into five stages, they

are

· Problem recognition

· Identity and formulation of this problem

· Data Collection

· Presentation

· Evaluation of information


25

The information retrieval and the question of the access under practical aspect was studied

briefly by Wilson .We can distinguish four practises from the Wilson approach and his

nested model Wilson (1999).

Figure 4.3: Information Retrieval practices

According to Wilson, the four types of practices are as follows:

4.1.2.1 Information Behaviour

It is the totality of human behaviour in relation to sources and channels of information,

which include both active and passive information seeking; also the information use .It

primarily includes face to face communication with others. For example, watching TV

adverts, without any intention to act on the information given (Wilson, 1999).

4.1.2.2 Information seeking behaviour

It is defined as the behaviour, which is purposely in sought of information as a consequence

of a need to satisfy some goal. The interaction with manual information systems (such as a

newspaper or a library), or with computer –based systems (internet)

4.1.2.3 Information searching behaviour

It is the micro-level of behaviour used by the searcher in interaction with the information

system, whether at level of human computer interaction (ex: mouse clicks on links) or at

higher level (ex: determining the criteria for deciding which is most useful between two

books selected from same shelf) to judge the basis of information retrieved.


26

4.1.2.4 Information use behaviour

This mainly involves the comparison of existing knowledge with the given information; it

consists of physical and mental acts based on the information found in the knowledge base

The works of Wilson (1999), suggest that the two types of behaviour (Information seeking

and Information use) when used as practises of access to information are regarded as sets of

actions and choices put in place for information retrieval and use .This type of approach

shows that the real needs of user and his environment has to be given prime attention.

The retrieval of information by a knowledge model was approached by Davies (1989).It

consists of four phases:

· Exploration of information world

· Interrogation of the base of information

· Information base analysis

· Preferences and individual discoveries based annotation

The definition of information need is advanced by the American Library Association (2011),

puts forward the bond of requirement in information and its use, It says “To be competent in

the use of information means that one can recognise when a need for information emerges

and that one is able to find information adequate as well as evaluation and exploiting it”.

Thus based on these principles we assume that the information needs of the user always

suppose an expectation and a use of retrieved information. In a situation related to a

decisional problem, the information needs would be lacking, as put forward by the Economic

intelligence .The search for information begins after this decisional situation in the mind of

the user.

4.2 Multimedia

In today‟s world, Multimedia means “more than one Medium”. To say this in other words,

books, movies are all some of the main examples of multimedia and they are the mixture of

text, images, music and video (Coorough, 2001).

4.2.1 History of Multimedia

It is hard to establish a specific origin date, but one of the initial and well-known examples

of multimedia is video game Pong, Nolan Bushnell developed it in the year 1972. Initially it

started as a portico game and it ended up in many homes (Solomon, 2004).


27

Figure 4.4: Representation of Multimedia in Today‟s World

Source: Mass Registration, 2011(Online)

Currently Multimedia may possibly be defined as the unified assimilation of animation,

audio, text, graphics and video, which provides a high level of communication and control

(Walker, 2000). The progression of multimedia is said to be the story of the advancement of

these technologies.

In the year 1970s, Desktop computers used in the home and office helped a lot in getting our

work done, delivers information and provide entertainment. There are some key technologies

that have contributed a lot in the progression of multimedia computers, which changed the

way we look at computers. At first computers were used to solve some of the difficult

mathematical problems, where they are used as a single purpose machines.

In the year 1976, Steve jobs and Steve Wozniak founded a new company called apple

computer and a year later they revealed Apple II, which is the first computer to use colour

graphics (Shuman, 2002). A new revolution has started in the computer industry and in the

year 1984 Apple released Macintosh with Graphical user interface (GUI). In the later year

Microsoft released its first version of windows operating system, this led to high revolution

in the field of multimedia (Vaughan, 2001).

Both Macintosh and Windows Operating system flagged the way for development of

multimedia, since both the operating systems handle sound and graphics developers started

to create programs that use multimedia for more powerful effect. Macromedia (previously


28

called Macro mind) is the only company that played a vital role in the Multimedia. Each of

the new developments that are made in each year is enhanced further in the next year,

making Multimedia more interesting, superior and faster (Lake and Bean, 2004).

In 1960s, mainframe computers are used, which manages huge financial systems and

databases (Rashmi, 2010). Where, In 1970s saw a big growth, where computer terminals are

used all over the organisations for managing information and publishing.

The 1980s desktop computers are used for spreadsheet, word processing and for playing

games. In the mid 1980s and 1990s, there seems to be advancement in the usage of

computers, developers started to look at how the computers can be used in the near future.

Few developments like high data storage capacity in disk drives increase in speed of desktop

computers, Digital video and audio, LAN and WAN that allows users to connect to the world.

Furthermore Hider (2006), says that Computer developers found that the multimedia

computers are used to increase the throughput and efficiency on the job, provide unique

information‟s that are needed and helps users to develop their knowledge in multimedia.

4.2.2 Features of Multimedia

According to (Feldman, 1994), There are two main features in Multimedia Environment;

they are Digital Environment & Interactivity.

Figure 4.5: Features of Multimedia

4.2.2.1 Digital environment

The term multimedia was in use before the usage of computers. This artefact certainly

offered multiple media types such as images, text and sound, but each of these media types

are delivered as a self-determining element. Electronic technology i.e. the digital

environment provides a single standard with the ability to integrate different types of

information‟s that are provided.


29

4.2.2.2 Interactivity

It is one of the most powerful features that is offered by multimedia, because interactivity

has one of the most effective advantage in the traditional system, some of the linear media

such as video or film, it is hard to believe that multimedia exponents put forward

interactivity as one of the essential component.

Interactivity is one of the best ways in which a user can browse and search through an

electronic database, where this process is more or less controlled by the software‟s that are

used.

4.2.3 Factors in which Multimedia can be affected

According to (Hashmi and Guvenli, 2001), there are four important factors in which

development of multimedia systems can be affected, they are

1. In need of very large memory storage

2. Handling of huge amount of information

3. Easy way of navigation

4. Output of images and sound must be improved to achieve the requirement level.

4.3 Multimedia Information Retrieval

MIR deals with finding the information on media types such as Music, images and videos

other than text. With the explosive growth of music, video and images that are available on

the internet; there is an easy access for the people to satisfy their information needs (Preez,

2004). In reality, the term MIR is not restricted to the retrieval of information. It covers a

wide variety of topics in information, which are associated with information retrieval that

includes information conversion, abridgement and categorisation.


30

Figure 4.6: MultiMedia Information Retrieval and Management

Source: Feng et al, 2003

The process given in Fig [4.6] explains the multimedia information retrieval and

management system, If a query is sent for retrieving a particular information, say for e.g.:

Images with size: 200kb and colour: blue, then the query is searched according to those size

and colour, then the images that are matched related to those query are retrieved and

presented to the user.

The earliest research that was carried out in MIR is based on the computer vision research.

Recently, researchers have started to move away from feature-based retrieval to content

based retrieval (Robins, 2000). During the continuous development of new techniques for

multimedia retrieval, researchers in this field have refined their methodologies, which

include information retrieval, databases, image and signal processing, Human computer

interaction, data mining, domain knowledge used for applications etc. (Hersh, 2009).

According to internet and mobile association (2009), main motive of MIR is to provide users

with the accurate answers they needed, in particular users express their information needs in

the form of queries and then the system matches those queries in the database to find the

information relevant those queries.

More effort has been applied to maintain the user‟s satisfaction by making the systems

human centred. There are many user‟s who have started to use different types of multimedia

through image search, Google video, AltaVista audio search etc... Lew et al (2006) pointed

out two main basic needs for MIR systems: they are searching and browsing. The methods


31

for achieving the needs falls into two main categories: feature-based and category based. At

present category based methods are becoming most popular, because they express the

semantics of media, which allows users for better retrieval of information.

4.3.1 History of MIR

In this section, I have briefly described the history of MIR and some of the research carried

out recently.

There is a gap between the devastating amount of information available and the human

factor for handling the data, this unfortunately leads to Information Overload (Maes, 1994).

People spend substantial amount of time to keep them entertained in their day to day life by

searching information through web pages, books, music, images, movies, news,

advertisements, etc. People need useful means to economically find the information they

need and to avoid the inappropriate information, as a result of this information access

technologies arise to meet the confront.

Subsequently information can be recorded as different data types, such as images, audio,

video and text, the retrieval system is able to retrieve the information from these varying

media types, this gives rise to the concept of Multimedia Information Retrieval systems.

Figure 4.7: Multimedia Information Retrieval Architecture

Source: Maghlaes, 2008


32

One of the major information access techniques is said to be information retrieval, the study

of information retrieval started in early 1960‟s and conventionally it focussed on textual

retrieval of documents (Yu, 2004). Recent years this has become widespread in the area of

research that studies the demonstration, data storage, organisation and access to variety of

information items such as video, audio, image, documents etc.

Therefore it is named as multimedia information retrieval (MIR). The initial goal is to

retrieve the relevant information in response to the queries given by the user. One of the

prominent examples is content-based image retrieval (CBIR) (Smeulders, 2000), where the

user is habitually required to provide some image examples to feed the system, where some

of the relevant images are returned by comparing visual similarities between the images

stored in the database and given examples. Let us discuss the current research in music,

image, video and Text retrieval.

4.3.1.1 Music Retrieval

In the past few years there has been an unprecedented growth in the field of music that is

made available through services such as iTunes, Napster, eMusic, etc. A normal user

consumes Gigabytes of data consistently in attempt to acquire the desire music data. As a

result, the field of music retrieval has had lot of attraction. Author Downie (2003), pointed

out many challenges to music information retrieval that includes the interaction between the

features such as pitch and tempo. The representation scheme determines the computational

costs, such as bandwidth. Author Byrd and Crawford (2002), believes that these methods are

used primarily for text IR and music IR is much more complicated as there is no proper

explanation on this retrieval process and their features (pitch, tempo etc...) in representing

them. One of the increasingly standard and popular querying methods for music

identification is query by hearing music. This method allows users to find songs by hearing

the music a small portion of it. For example: Sony Ericsson has song finder portability,

where user can able to find songs by listening to music.

In his earlier works (Ghias et al, 1995), Focuses primarily on monophonic data and uses

those pitches in the melodic track for representation. In this, user input data is converted into

a symbolic form that is based on the pitch and this form is used to search the MIDI music

database. Author (Pickens et al, 2003), expands this querying technique to deal with

polyphonic music data. He carries out a language model framework which is used to retrieve

the music performed by piano or by any other methodologies Recent work has been done by

(Hijikata et al, 2006) on the Content-Based filtering system, which gives privileges for users

to edit their own profile without hampering the representation. Furthermore he created


33

decisions trees to gain inference on the kind of music gained by the user and also varying

features like tempo and tonality.

4.3.1.2 Image Retrieval

In recent years, digital photography has taken the driving seat in photography and this drives

the need to find an easy and efficient search technique. It is easy to find the image with a

description rather having to look through all the images. In 1970s, the concept of image

retrieval started with research in computer vision and database management. In these early

days and up to last 15 years, the main method for searching was to annotate the image with

text (Rui et al, 1999). The content based retrieval in multimedia IR has been heavily

researched recently. (Smeulders et al, 2000), classified image retrieval application into three

categories:

1. Search by association – To find new interesting images

2. Targets the search – To find a new specific image or object.

3. Category search

Figure 4.8: Multimedia- Image Information Retrieval and Management

Source: Feng et al, 2003

The above figure [4.8] explains the process of image retrieval, where the images can be

searched with the help of refined search. E.g. If we search for a particular type of image with

size and type of file we can able to retrieve those images from the image database according


34

to the file type and size. Furthermore, we can select the image visually and query can be

given with the help of same name from the image that has been seen visually and the related

images can be retrieved from the image database.

Corridoni et al. (1999) retrieved images based on colour semantics such as warmth, contrast

etc. This system allows the user to specify the colour semantics and finds images that match.

Kato et al. (1992) developed a system, which takes the sketch done by the user and finds

similar images. Bujis and Lew (2003) developed image scrape applications, which allows the

user to sketch in images and finds similar images. Natsev et al. (2004) used multiple

signatures per image for computing the similarity between the given image and images in the

database.

(Chang et al, 1981) showed that a statistical learning method helps to improve the

performance of visual information retrieval system. They found the need to introduce new

algorithms to deal with sparse training data and imbalance in the type of training data. Rui et

al. (1999), added relevance feedback to their MARS system in order to improve the search

results. Tieu and Viola et al. (2004), created a framework that uses many features and

boosting algorithm to learn queries through online.

4.3.1.3 Video Retrieval

Video retrieval aims to find the desired video. Like image retrieval some of the earliest

approaches were to annotate video data and use standard IR techniques such as YouTube and

Google. However, annotation is impossible with collections that are automatically from

broadcast or other means. So, automatic techniques were needed. Wactlar et al. (1999)

created a terabyte sized video library and used automatically acquired descriptors for

indexing and segmentation. Sivic and Zisserman (2003) made the comparison between text

IR and video IR. Their goal was to create a fast system that works on video as well on text as

Google does. They compared with many features and found some problems. But the analogy

to text IR worked well. The important parts of video retrieval are segmentation and

partitioning (Aslandogan and Yu, 1999). Zhang et.al, (1993) used multiple thresholds on the

histogram to detect gradual transitions and camera breaks. Gunsel et al. (1998) looked at the

use of syntactic and semantic features for unsupervised content based video segmentation.

Sebe et al. (2003) used new techniques such as list semantic video retrieval, learning and

feedback strategies and interactive retrieval. The following are the researches done by using

these three techniques. Naphide and Huang (2001) used a probabilistic framework to map

low level feature into semantic representations and semantic representation is used for

indexing, searching and retrieval. Snoek et al. (2004) developed a concept lexicon to achieve

good performance in 2004 TREC Video Track. Browne and Smeaton (2004) incorporated


35

various relevance feedback methods and used object based interaction and ranking. Yan et al.

(2003) used negative pseudo relevance feedback for the 2002 TREC Video Track. This

approach increased performance over standard retrieval. Yan and Hauptmann (2005)

introduced a boosting algorithm called Co-Retrieval. Gaughan et al. (2003) developed a

system that incorporates speech recognition. Girgensohn et al. (2005), builds a system

focused on the user interface. Their system was one of the best in TRECVID.

4.3.1.4 Text Retrieval

Text retrieval (also called as information retrieval (IR) or document retrieval (DR)) licenses

access to documents based on the gratified of the information. These documents may be

detained from huge amount of document bases. For example (Stein, 1991) quotes Library of

music which has a collection of approximately 30 terabytes. In this information retrieval

systems, users start searching their information by entering the approximate query, the

system replies by searching the entire document bases for the documents that match the

query given by the user and those documents are turned out to the user. The next evolution

of text retrieval was semantic based information retrieval.

4.3.1.4.1 Text based application for Information retrieval

Text based applications are used to analyse the huge variety of text documents , some of the

applications that are used early includes the creation of Information Retrieval Systems (IRS)

to analyse and retrieve the information needs. According to (Kim, 2011) some of the early

text based applications that are used to retrieve the information are:

1. Legal documents and digitalised medical journals

2. Insurance documents

3. Translation of language and program collation

Due to the increase in Internet user base, text based applications have switched to public

domain. Such commonly used applications are E-mail, Search Engines, Education, and

Business etc…

According to (Jarvelin et al, 2001), there are two ways to locate the text documents

1. Direct – Collection of query term that can be matched with the document

database and the information relevant to the query is retrieved.

2. Indirect – With the help of metadata that described the data in the document.


36

4.3.2 Multimedia Semantics

Multimedia Semantics is the meaning illustrated inside the music, videos, images etc. and

the semantic multimedia database (SMDB) systems are projected to assimilate semantic

information of a wide range of formats, which includes text, animation, graphics, audio,

video and images. It plays a vital role in the retrieval of the multimedia data‟s (Angelides

and Dustdar, 1997).

Figure 4.9: Semantic Multimedia Database Architecture (SMDB)

Source: Li, 1999

4.4 Mobile Multimedia Information Retrieval

Mobile multimedia refers to the interchange of multimedia information through wireless

Internet or wireless networks (Curwen and Whalley, 2011).

4.4.1 Wireless Communications

Wireless communication started to emerge in the early 1930s during the Second World War

with the use of “Walkie- talkies”, which enabled them to stay connected with the

headquarters (Elliott and Philips, 2004). In the year 1946, AT&T Bell initiated the first

commercial radiotelephone service in the US, which allowed communication between pubic

fixed networks and users in the cars. In the year 1960s, Bell Systems launched the Improved


37

Mobile Telephone Service (IMTS), which laid the foundation for commercial -sector mobile

communications (Garg, 2007).

According to (O‟callaghan, 2003), Wireless communications have grown successfully in the

past 20 years and it is expected to develop further in the years ahead. Rackley (2007) says

that advancements made in microprocessor technologies enabled the beginning of reliable

wireless communication systems and it is said to be first generation.With the organization of

services such as mobile multimedia, mobile video applications and mobile streaming on

demand, the requirement factor is increasing for higher data rates in the third-generation (3G)

mobile cellular systems and this trend continues to evolve in the Fourth generation (4G)

systems.

Figure 4.10: Wireless Communications

4.4.1.1 First Generation 1G

The first generation wireless technologies, also called 1G (uses simple analogue signals).

Mobile phones based on this technology are mainly used by government agencies and

military before this technology came into general use (Elliott and Philips, 2004).


38

4.4.1.2 Second generation 2G

The popularity of wireless networks started to grow in the late 1980s and early 1990s that

resulted in increasing demand for network capacity. With these disadvantages of analogue

1G systems, this led to the growth of second generation wireless system based on the digital

technology. Second generation networks also referred to as Global System for Mobile

Communications (GSM), it varies fundamentally from 1G system because of the use of

cellular network architecture (Stallings, 2004).

GSM is still used by all European countries and also been vicarious to other continents,

includes Africa and South America. There are over 540 million subscribers in Europe (GSM

Europe, 2005). With GSM it is possible to send and receive limited amounts of data via

Short Messaging Service (SMS) and mobile browsing via the wireless Applications Protocol

(WAP) (Elliot and Philips, 2004).

4.4.1.3 Second and half generation networks 2.5G

2.5G technologies characterize a state of development that connects 2G and 3G. In the year

1990 and early 2000s transmission rates are entitled by General Packet Radio Services

(GPRS).The transmission speed of data‟s are now 10times faster with 115kbits per second

based on packet switching technology (International Telecommunication Union, 2003).

Packet switching modifies the use of bandwidth available in a network and minimises the

time it takes for the data to travel across the network.

4.4.1.4 Third Generation Networks (3G)

Third generation mobile telephony (3G) is the inheritor to the 2G and 2.5G systems.

Advancements made in 3G are said to be one of the salient features that provides enriched

security and encryption features, enhancement in screen display and the ability to handle the

multimedia data (graphics and video streaming). 3G allows data‟s to be transmitted faster

with the rates up to 1920kbits per second. These technologies were introduced first in Japan

in the year 2001 and later it established widely to Europe and the USA in 2002. UMTS

(Universal Mobile Telecommunications System) is the third generation mobile phone

technology used mainly in Europe and Japan (Elliott and Philips, 2004).


39

4.4.1.5 Problems faced by wireless multimedia

Wireless network access are required for mobile computers, they are a bit difficult to achieve

than wired communication because of the surrounding environment that interacts with the

signal, resulting in blockage of signals paths and introduces noise and echoes. Hence, the

quality of data connectivity could be lower than wire connections at some points. Lower

bandwidth, less stable connection and with a highly varying quality affect communication

latency. According to Lopez and Roman (2009), the key problems in wireless multimedia

systems are

1. Quality of service

2. Limited energy resources

3. Heterogeneous environment

4.2.2 User Application of Mobile Multimedia

4.2.2.1 Introduction

The mobile industry has had tremendous growth on the multimedia field. First, multimedia is

the basis for development of mobile technology. Second, there is little growth on the markets

of calls and messaging. Average gain per user has declined as technology improved and

competition enhanced. According to (Pok and Teo, 2003), Mobile multimedia highlights the

twofold uses of mobile phones: connectivity and content. Mobile phones are primarily used

for telephone conversation and messaging (connectivity). Nowadays mobile services such as

ring tones and caller tunes have become popular (content). Especially user generated mobile

multimedia challenges established concerns. For example, photo-blogging supports active

connectivity to others by sharing content. Capturing and sharing of information are the

possible applications of multimedia as camera and MMS. Users are free to invent

applications within certain technical limits such as camera resolution and bandwidth.

Capturing has become more popular than sharing as people use their phones as cameras

instead of photo-messaging devices. Internet technologies shows multimedia incorporates in

various directions (Carlsson et al, 2005). World Wide Web shows that there is abundant

range for technologies that support interpersonal connectivity and commercial services. In

short, multimedia applications such as streaming data, visual radio, interactive television and

multimedia blogging are accepted in the market.


40

The following sections reflect mobile multimedia based on experiences gathered in research

projects at the National Consumer Research Centre in Finland (2011), which is an

interdisciplinary independent government research unit organised under the Ministry of

Trade and Industry. In order to be proactive and support the development of innovations, the

research has been both experimental and monitoring. The combination of these two

approaches guides us to make interpretation on future practices connected with mobile

multimedia. Emerging user applications are developed into commercial services, platforms

and handset features for mass market.

4.2.2.2 Experimenting with users

The mobile industry lacks user-producer community‟s fact in the Internet. Due to this,

product development has been conduct for industry and users are adapted to the framework

rather than expanded it. WAP - Wireless Application Protocol is the obvious failure of this

approach. SMS is the wide technology that is for specific communication purposes.

Multimedia offers similar potential as SMS. Therefore, it is very important to carry out

research on the social, technological and business implications of the use of multimedia

(Kopomaa, 2000). Their research carried out relates to the invention of meaningful uses. An

explorative approach is used to study how users adopt streaming video. Koskinen et.al (2002)

used similar approaches on multimedia messaging and video messaging. So the researches

have been able to describe experienced usefulness and use of social and interactional patterns.

A successful advance in social studies on mobile telephony has not translated into

multimedia domain. This is largely due to dispersed nature of the development and adoption

of multimedia.

4.2.2.3 Adopting commercial services

Introducing meaningful applications will attract the users toward mobile multimedia. In

Large scale, it is necessary to attract technological development and investments. For

number of years the mobile services on Finnish market have been monitored (Rogers, 1995).

This approach stems from diffusion and acceptance theories and is a popular approach in

system research on mobile services (Pagani, 2004). Finland has been one of the leading

nations during the GSM era. Being the home country of the multinational handset and

network supplier Nokia, many innovations are launched early in Finland. Mobile services

like digital television and visual radio are functional in Finland. Our results challenge

established business strategies for mobile services.


41

Furthermore users prefer flexibility to efficiency. On the other hand users prefer the services

that is cheap and user friendly. Results show that finding mobile services is still talking place

in Finland. The relevance of monitoring the overall adoption of mobile services is twofold.

First, the overall popularity of mobile services is viewed; second, it shows the relative

popularity of different services. This approach is really helpful for multimedia applications

in mobile technology.

4.2.2.4 Multimedia Messaging Service (MMS)

Multimedia Messaging service (MMS) is a new revolution in mobile messaging. It is

similarly like SMS (Short Messaging Service), MMS it is one of the ways to send a message

from one mobile to another (Pesch, 2008). The main difference between MMS and SMS is

that, in MMS it not only consists of text, but also includes audio, video, images and sound.

Further advantage is that MMS messages can be sent from a mobile phone to an email

address.

Some of the formats that are entrenched within MMS include:

Text (colours, Format, fonts etc...)

Images (GIF and JPEG formats)

Audio (MP3, MIDI formats)

Video (MPEG)

Images can be selected and downloaded from WAP sites within the phone, or may be taken

from the phone with the help of built-in camera.

According to Efremidis et al (2011), MMS message is not a collection of attachments it is a

single entity and it is an extension from SMS protocol. One of the main ways to differentiate

SMS and MMS messages are, SMS message are restricted to 160 bytes, whereas MMS

message has no size limit and can be many kilo bytes or even large in size. To support such

large Messages to be delivered from one mobile to another there must be a third generation

(3G) network, even though smaller messages can be sent with second generation (2G)

networks with the help of GPRS.

The first MMS enabled phones started to emerge in the year 2002, and their looks attracted

the users, which is said to be used very extensively in the future years (Chiu and Lin, 2011).

Different MMS technologies are used by different manufacturers in different ways, for

example Nokia introduces their phones with direct MMS facilities, whereas Sony Ericsson

introduces phones that have enhanced messaging service (EMS).


42

4.2.2.5 Enhanced Messaging service (EMS)

EMS is an intermediate between SMS and MMS, which provides some of the characteristic

facilities of MMS (pictures, Audio such as ring-tones, structured text and some animations).

This technology is designed by Sony Ericsson and is said to work with prevailing networks.

4.4.3 Mobile media

It is a kind of word that we use regularly in our day to day life, it is a well known fact that

mobile phones have developed greatly to support text, music, video, etc. Print media

(newspapers and magazines) was one of the dominant features of information in the past, but

today, with cell phones, tablet PC‟s, iPod‟s and laptops dominate in this generation, which

enables us to read new, watch video clips, listen to music. Hence, all the three types of media

can be accessed through those (Hall, 2011). We can say that mobile multi-media are one of

the dominant fields at present, which presents a new way to communicate. The development

made in this medium is one of the easy accesses for the mobile users to communicate,

listening to music, and take video or pictures through mobile.

Figure 4.11 : Mobile Media

Source: Prosyst, 2011 (Online)

4.4.3.1 Mobile Internet

Mobile internet normally refers to the web when accessed from a mobile device like a smart

phone and the development has been skyrocketed in the recent years. Progression in mobile

technologies are said to be one of the promising and additional benefits by decreasing the

spatial and time based constraints, in many developed countries mobile phones are said to be

one of the intimated part in everyday‟s life and majority of people carry on with them all the

times (Jansen et al, 2005). As the use of 3G propagation, the usage of wireless internet

started to become increasingly popular. Jansen et al (2000) say that, the traditional usage of

accessing internet in PCs such as web Browsing, e-mail, chat or entertainment are made


43

available through a mobile device. In reality the primary digital difference between the PC

and mobile internet is their pervasiveness (Okazaki and Romero, 2010). The rapid growth of

smart phones and other mobile devices made a great evolution on mobile web technology.

Experts have predicted that mobile devices will soon overtake the Desktop computers as one

of the trendy way to access the internet.

4.4.3.2 Smart phones

The birth of smart phones made a big revolution in the internet world, several functions are

combined into one device which includes mobile cellular telephone, a personal digital

assistant, and currently it can also serve as an mp3 player, web browser, navigation system

and many other things (Schiller, 2003). Even though there are few problems faced with their

screen sizes, slow downloadable speeds etc… they said to overtake the desktop computers

with the same functions being performed through smart phones.

4.4.3.3 Evolving Features

After the invention of mobile devices the popularity of internet usage seems to be one of the

dominating factors and eventually it became one of the key features of mobile devices. With

the advancement made in apps and programming platforms, smart phones has essentially

become one-stop-shop for all modern amenities. Mobile enhanced websites and apps have

brought a new experience in the web from our mobile devices. There won‟t be any further

issue that our speed of internet is low, size of screen is smaller because web developers

started to work on those issues. Touch screens, accelerometers, and GPS locating seems to

be one of the special features of mobile web, where these cannot be offered in PCs.


44

Chapter: 5

Research Questions

In order to propose a solution to the problems faced in Multimedia Industry regarding

Information Retrieval (IR), a comprehensive research has to be taken. Survey is designed

and developed in accordance with the research that has been carried out in multimedia

retrieval and user information needs. This Survey is conducted with 40 participants between

the age group of 20-27. With the survey results, the problems are identified and an effective

methodology has to be designed to execute the research successfully.

This survey is conducted mainly to analyse the problems that are faced by the mobile users

and some of my research findings motivated me in conducting this survey, they are:

How can the information needs of users be met?

Do they try to use the advanced features that are available?

Are there any characteristics difference between users who incline to search

compared to users?

In particular Browsing through mobile internet is still the predominant form of

information access?

How do we facilitate user‟s access to multimedia information?

The kind of information that the searchers look out for and the way to simplify user

access to multimedia information?


45

Chapter: 6

Methodology

Methodology is a precise way of presenting an operation that implies some of the specific

deliverables at the end of each process.

6.1 Survey

In this phase, the steps needed to be taken to execute the research are created.

Conducting Surveys is the core part of this project as the entire solution to be proposed

revolves around the feedback received from the users who have participated in the Surveys.

The Process shown in Figure [6.1], explains the way in which methodology is going to be

carried out. In this project the methodology is split into Survey Design and Survey

Implementation, where the design phase explains how the survey is designed and on the

basis in which they are going to address the problems, while the implementation phase

explains the tools and samplings used for the survey.

Figure 6.1: Methodology process

6.1.1 Survey Design

Research questions and literature review played vital roles to design and develop the survey.

The problems and challenges in accessing the variety of media types or in search of

information on particular media types through mobiles are discussed in literature review.

With the help of research questions and literature review, survey questionnaires are framed

for in-depth analysis of the problems faced by mobile users. The questions are designed in

such a way that it addresses all the problems that are faced by the mobile multimedia users

and their information retrieval process.


46

6.1.1.1 Survey Definition

The questions that are to be executed are defined in this stage and are made sure they are

relevant to Information Retrieval, MoMIR and Multimedia. They are designed in such a way

that the questions correspond to the current trend in the Multimedia industry. A lot of

research is done on framing the questions. In order to make the survey effective, we need to

understand the exposure of a common user to today multimedia devices.

For example, asking questions about sophisticated technologies and using complex

terminologies will not help the user in answering questions effectively. The questions are

framed according to the high level knowledge of users on Multimedia devices and

Information. The questions needs to as simple and straight forward as possible and also

extract information that is relevant to this research.

6.1.1.2 Generation of Questions

Before beginning the survey process, initial background of the participants were collected

(see Appendix C ), including their way of browsing, the query they give to find information

on any media types, their proficiency level in accessing the mobile web and most

significantly, whether they have used any multimedia search engines before.

My next focus is on designing the survey questions (see Appendix D) and my primary focus

is to know the Make of the mobile, their design features and the purpose behind to buy those,

where we can understand on what basis the mobile phones are used.

My next question focuses on the types of search engines that are used for downloading or

accessing the media types such as Audio, Video and Images, where I can get a clear view on

the search engines that are used for accessing or retrieving the information on media types.

This will pave a way for analyzing the problems caused in handling the multimedia content

and the factors that affect them mostly when using multimedia apps in mobile phones.

To identify the problems further, next survey question is designed to know the data types

(Audio, video and images) that are least compatible and the features that are commonly used

in mobile phones.

Finally to know the future expectations of mobile phones, my next question focused on how

mobile phones can be made user friendly in accessing the multimedia web sites.


47

6.1.2 Survey Implementation

This is the first and an important step in the entire process. The two main operations in this

project are sampling for the Survey and Survey execution. In this project, I have chosen

„Survey Monkey‟ as the tool for survey execution and Microsoft Office applications for

documenting the feedback received and for reporting purposes.

Figure 6.2: Survey Implementation process

6.1.2.1 Survey Monkey

This is one of the tools available in the web for creating online surveys. Since this is a web

based application, it is accessible for non-technical people and it is easy to participate.

Unlike other tools, the main advantage of Survey Monkey is its feature set. It is extremely

easy to arrange questions according to user liking and can be transformed to various formats

like HTML, CVS and SQL.

The tools is also economical for research projects, as it is free of cost and very time saving in

while conducting One-on-One interviews. Survey Monkey is a flexible tool for creating

survey questions and also for accessing the results of survey. The tool also includes reporting

and analysis capabilities.


48

Figure 6.3: Survey Monkey, 2011 (Online) http://www.surveymonkey.com/

6.1.2.2 Sampling for the survey

After the design of survey questions, finding the sampling for survey is one of the

challenging tasks, because participants need to be targeted with the particular age group.

My initial plan was to conduct the survey with 50 participants, but it ended up with 40.

Participants are targeted between the age group of 20-27 and from different countries,

including UK, China, India and Nigeria.

Reason behind targeting the particular age group is to get the reply significantly and

precisely, moreover high levels of mobile users are in that age group. According to a report

by Digital media across Asia (2009) as of June 2006, 94% of mobile phones are used in the

age group of 18-24 and 91% in the age group of 24-27.

6.1.2.3 Survey Execution

Survey Monkey provides a declarative way for creating surveys. For this project, surveys are

sent to common users between the age group of 20-27 and from different countries through

email and social networking websites.

The answers given by the users for the questions in survey are sent back to the Survey

Monkey web service. It is possible to analyze the results of the survey through the in-built

reporting capabilities of Survey Monkey

http://www.surveymonkey.com/


49

6.2 Ethics

This project is carried out in a proper ethical way by interacting with the variety of people

from different countries in order to analyze the problems that are faced by the mobile users

in accessing different media types. All research and survey process are followed in a precise

way through highest ethical standards without exploiting others or breaking the ethical rules.


50

Chapter: 7

Results

In this section, I have given a detailed explanation of the process that was involved in finding

a solution to the Information Retrieval problems identified in the Design and Implementation

of the survey.

This is a crucial phase in finding the solution to the problems faced by users in Mobile

Multimedia Information Retrieval (MoMIR). Let us analyze the variety of problems that are

faced by the mobile users in retrieving the Information from the survey results (see

Appendix E).

7.1 Analysis of the Survey

7.1.1 Participants background and Knowledge

As discussed in the section (6.1.1.2), the participants were selected between the age group of

20- 27, belongs to different countries and majority of them were students belongs to MSc –

Information systems management and MSc- information systems course at Sheffield

University.

The results gathered from the initial questionnaire (see Appendix C), aimed to analyse the

background information of the participants and it proves that the participants are familiar

with using mobile web-based search engines. Interestingly many participants use the mobile

web daily (see Appendix C (Q.3)) and the rest of them have a usage frequency of once or

twice in a week. Furthermore, the level of using the internet is said to be intermediate and the

most popular search engine among them was Google (see Appendix E (Q. 3)).

7.1.2 Choosing Multimedia Mobile Devices

In the survey taken, the problem of finding the right mobile device for handling multimedia

data was discussed. There are many key factors in mobile devices that support the usage and

handling of multimedia content in mobile. Some of them are operating system, ease-of-use,

functionality, size memory and processor.


51

There is a mix of software and hardware that plays a role in multimedia handling. According

to the survey, most of the mobile users feel Ease-of-user, Appearance and Operating system

as the key factors for choosing a mobile device for enjoying multimedia content.

Figure 7.1: Representation of Design features rated highly by mobile users

Ease-of-use is always a priority for a common user for handling multimedia content. A

device that is not easy to use cannot impress the user even though it might be having

powerful hardware and software technology built into it. Appearance is also a key, as form

factor is one of the main considerations for common user in choosing the mobile device.

Operating System is the key in connecting the hardware and the software. It is responsible

for creating a responsive interface between user and the device. The performance of the

device when using multimedia content is greatly influenced by the operating system.

7.1.3 Choosing the best Multimedia Web Services

One of the highlights of today‟s web is the handling of multimedia web content (images,

audio & video). There are lots of multimedia web services available for handling multimedia

content and choosing the right service depends on factors like interface, speed, reliable and

efficient. A survey (see Appendix E (Q. 4, 5, 6)) was taken to find out the preferred

multimedia websites and to discover the reasons behind choosing them.


52

Figure 7.2: Website used for viewing and watching/ images and videos

Images play a big role in multimedia industry. Nowadays, most of the users capture images

digitally and digital imaging technologies have grown rapidly in the recent years. There are

websites available to handle large volumes of images and share it among users anywhere in

the world. Some popular services are Picasa, Flickr, Photo Bucket, Image shack, Tiny Pic,

Picasa and Flickr was the most used image handling websites. After further research on the

survey, the main factors considered by the user is Easy-to-use, interface, image editing

features, free space offered, complete sharing options, integration with other services like

email, social networking, etc.

Similar survey was taken to identify the best websites for hosting and sharing video content.

The usage of video content on the web has increased significantly over the years (See Figure

7.2). This is mainly due to the increase in the bandwidth offered by the internet service

providers. Five popular video hosting websites contested in the survey and YouTube

emerged as the clear winner. The main factors considered here was sharing option (upload

and download), integration with Google services and user-friendly interface.

7.1.4 Multimedia features widely used in Mobile Phone

MMS was the earlier multimedia feature in mobile phone used for transferring multimedia

content. But this trend changed drastically due to the emergence of new technologies.

Sharing and retrieval of information has become fairly straight forward due to mobile

multimedia retrieval technologies facilitated by multimedia content hosting websites.

A survey (see Appendix E (Q.9)) was taken to identify the most widely used multimedia

feature or operation done using mobile device. The results of the survey are shown below

(Figure 7.3). Interestingly MMS is the least used feature today as music, social networking

and navigation has taken the centre stage. Due to the significant improvement on the mobile

OS, audio file handling, processing and retrieving have become very easy. Navigation is also


53

being supported in mobile devices due to the efficient data retrieval software‟s and

advancement in mobile/wireless technologies.

Figure 7.3: Features mostly used in Mobile Phones

7.2 Problem Identification & Investigation

Factors affecting Multimedia content in Mobile Phones:

In recent years, mobile phones have evolved to a great extent. Unfortunately, mobile phones

are not yet the perfect devices for processing and retrieving multimedia contents. There are

some constraints which make it hard to handle multimedia content as good as a PC does. A

survey (see Appendix E (Q.7)) was taken to identify the key problems faced by the user

when using multimedia content in their mobile phones. The result of the survey is shown in

Fig (7.4).

Figure 7.4: Key problems faced in using Multimedia Content

From the graph, it is conclusive that the main issue faced by the user is with the Browser and

Operating System. The browsers built in the mobile phones are responsible for viewing

multimedia web pages and retrieving data from the web. When these browsers are not able to


54

render webpage properly or optimize the content when zooming in or out, then there is a

difficulty in viewing multimedia content. To some extent these browser rely on the mobile

OS as well. The OS is heart of the mobile software which gives the power to the applications

to process multimedia content and retrieve the data from the device storage. From the graph,

it is evident that mobile OS still need improvement in this area.

7.2.1 Incompatible Data Types

One of the main problems faced by users today in processing multimedia content is the Data

Types. Due to a large variety of data types available for images, videos & audio it is hard for

devices to be compatible to all of them. Retrieving information from these data varies

significantly and this causes confusion to the users. A survey (see Appendix E (Q.13, 14, 15))

was taken to find out the least compatible multimedia data types in mobile devices for

processing and information retrieval.

The results of the survey are given below Fig [7.5] indicates the least compatible data types

of video, audio and image files respectively. From analyzing the survey feedback, the

compatibility of data types varies with different mobile devices. Different mobile devices

have conflicts with different data types. The conflict is very high as far as the Video content

is concerned and similar case for image content as well. But in the case of Audio

types, .wmv and .wav are compatible in almost all the mobile devices. Hence there is not

much conflict in the handling and process of audio data types in the mobile devices.

Figure 7.5: Represents the least compatible data types (Video, Audio and Image) in mobiles


55

7.2.2 Consequences of using Multimedia Application in Mobile

Phones

Using multimedia greatly affects the performance of the hardware used in mobile devices.

The software thrives on the power of hardware for performance. Running native multimedia

application or web based application on these devices can have some effect on the hardware

used. A survey (see Appendix E (Q.8)) was taken to find out which hardware is affected

most by multimedia usage. The results of the survey are shown in Fig. 7.6

Figure 7.6: Factors affect when using Multimedia apps

The battery takes the biggest hit when multimedia applications are used in mobile phones.

Processing of multimedia content consumes more memory and power. This inevitably drains

the batter sooner than non-multimedia applications. Since more memory and processor is

dedicated to handle multimedia content, there is a significant decrease in speed of other

applications. As a result, multitasking capability is compromised.

Due to these drawbacks in Mobile Phone, even today most users prefer PC for handling and

processing multimedia data. The same multimedia content is handling more quickly and

efficiently in a PC than in a mobile phone due to its lack to processing power and memory.

This trend could change in the future as more smart phones come into existence with larger

memory and more processing power. It is an undeniable fact that mobile phones have

evolved so much that it will not be used just for basic calling and messaging functionalities.


56

Chapter: 8

Discussions

8.1 Solution Discovery

8.1.1 Enhance Primary Mobile Multimedia Operations

In Today‟s world, information retrieval is intensely used for many multimedia related

operations. Not all operations are popular in mobile multimedia devices. A survey was taken

to determine the most used multimedia operations in mobile devices. The results of it are

shown in (see Appendix E (Q.9)).

From the graph shown (Figure 7.3) it is evident that Music, Social Networking and

Navigation are the most used multimedia related operations used in mobile phones today.

Hence it makes complete sense to pay more attention to the multimedia data that are

primarily used for these operations. Nowadays, users are not interested in sharing

multimedia content through MMS; instead they opt to share it via social networking websites

or image hosting or video hosting websites.

8.1.2 Mobile-Friendly Multimedia Websites

Having a single website which displays

multimedia content (images, videos, audio &

flash) for both PC and Mobile devices was

not very efficient due to the varying size of

display and configuration. This method was

also difficult to users for navigating the

WebPages in their mobile devices and it was

difficult to retrieve information efficiently

from these incompatible WebPages. Hence

there is a great need for creating separate

mobile versions of multimedia websites.

Figure 8.1: User‟s perspective on Good mobile friendly website


57

There are many factors that are to be considered while creating mobile compatible

multimedia website to facilitate information processing and information retrieval in mobile

devices. A survey was taken to determine the key factor that needs to be considered for

creating mobile-friendly website. These factors should enable the devices to handle

multimedia content and retrieve data efficiently. The results of the survey are shown in Fig:

8.1.

From the survey, it is evident that Content that is displayed in the mobile-friendly website

must be optimized and should be usable by users through their mobile devices. The webpage

should also be easy to navigate and should be completely compatible with mobile devices for

handling multimedia content.

8.1.3 Unify Multimedia Data Types

The problem of incompatible data types was explained in section (7.2.1) it is very difficult to

create mobile technologies to be compatible to all available data types in the web. This is

equally confusing and frustrating to a common user who has little knowledge about these

various data type the device has to deal with in order the process the multimedia data.

Information retrieval is very difficult to manage between these different devices as they are

stored in their mobile native formats.

Unifying all the data types in the future could be an expensive option, as there are various

reasons behind the existence of each data type. For example, mp4 is compatible with all

Macintosh and IOS devices but not greatly supported in Windows Devices. There is a

possibility of creating a common codec that could make Compatibility Bridge in these

devices. Making the device manufacturers to show real effort and interest in finding a

common intermediate codec and working their devices towards it will be a challenging task.

The confusion among users and incompatibility with devices will grow as more number of

data types is in existence.

8.2 Reflective Analysis

Challenges faced by the multimedia information retrieval are connected with the metadata,

which represents the content of multimedia. In multimedia information retrieval, the user

submits a query that is compared to the image on the system by their metadata. In most cases

of image retrieval, a user provides semantic words to refer the image. The image

characterizes denotative and connotative message. Denotative means an image an image


58

refers to the literal meaning has given by the dictionary. Connotation refers to the

associations that are connected to or suggested by the image. The connotation depends on the

situation of the transmitter and the receiver of the image (Yon 2008). An image may

generate different connotative meanings depending on image viewer‟s context. The

connotative need may have an implied meaning to the user. Connotative needs pose several

problems as it is the impression and the sensation of the users that guide information needs.

The connotative meaning is the image characteristic that is not easy to represent during

indexing process. “Because of the concept that connotative attributes of an image is subject

to an individual view‟s interpretation, when developing image representation schemes the

connotative messages are ignored” (Yon, 2008). For multimedia information, the need to

express information is subjective; their representation requires consideration of denoted and

connoted aspect; Denoted aspect enables us to consider something and connoted aspect to

imagine something from multimedia information.

The connotation aspect of Multimedia Information (MI) is often ignored in information

retrieval system. The image is represented using low level descriptors (texture, color...), the

user specifics his needs with semantic words. The interpretation given by the user to the

symbol of an image in MI is a problematic. Semantic and linguistic information associated to

a perceived component of an image is not the same for all users. The needs of users are

expressed semantically whereas the description of MI is done in relation to the specificities

of each medium in the system.

8.3 Problems Encountered

My first plan was to develop an interface that could retrieve the information given by users,

but developing an interface combined with all the types of query methods for variety of

media types will be too complicated and it is not practically applicable from the users‟ point

of view.

Initially there are variety of approaches were considered, but the fundamental intention of

this study is to analyze the problems faced by the multimedia mobile users. Primarily it is bit

hard to analyze the problems faced by the users who uses a variety of media types (Video,

audio and images). Moreover it is really tough to analyze the browsing facilities that are

allowed by the network providers, the mobile device that they use, the way of search they

carry out for finding the information for particular media types and the way they enter their

query for searching the information.


59

To put all these factors mentioned above into consideration, it was decided to take the survey

with the variety of mobile users to analyze their problems faced with the multimedia in their

mobile. The main aim of this survey is to focus on the problems with the multimedia (Music,

images, video and text). In this step, the problems related to Information retrieval are

extracted from users through the survey. These problems are discussed with users in detail

and the methodology is designed according to problems that are encountered.

Moreover the time allocated for my project is not sufficient because of the time delay in

gathering the problems faced by users in mobile. There are different thoughts from different

people and to analyse the thoughts and gather all the problems faced by the mobile users was

a challenging task tackled in the project.

After a widespread research and repeated trial and error method in conducting the survey

with the variety of mobile users was completed successfully. Defining the problems

encountered by variety of mobile users was really challenging because of the opinions given

from various mobile users vary on their own perception, furthermore summarising the

problems is also one of the challenging task. From the survey process, proposing a solution

for future directions is the most challenging task of the project. In the discussion of results

and conclusion phase it is a really tough task to suggest future recommendations of

multimedia information retrieval, but I somehow managed to write those effectively.

In the overall project schedule the time allocated for the survey was increased and to cope up

with that methodology was completed early, moreover it is really easy to complete after

analysing the problems.

8.4 Evaluation

Some of the most recent evaluation research carried out in multimedia information retrieval

is the TRECVID evaluation. In this TRECVID, there is a close contact between the

academic research and private industry, where the test is carried out in reality basis; this

attempt is preceded to provide the best quality of video retrieval systems. The main potency

in this retrieval is gathering the user information needs with the variety of query types given

to find the particular information.

This type of testing the data includes video with speech transcripts, translation of non-

English speech through machine, and a collection of multimedia topics (text, video, and

image) etc… Key frame based retrieval technique is one of the most trendy in video retrieval


60

systems, where the video is represented as a small collection of frames that is observed from

the video content (Pickering and Ruger, 2003).

Smeaton and Over (2003), discussed a complete evaluation techniques carried out in video

retrieval systems, which takes into account the usage archetype, compares a wide collection

of participated systems. Furthermore, evaluating the retrieval of multimedia is one of the

ongoing challenging problems. Audio, Images and Video share a distinct feature such as

content-based queries.


61

Chapter: 9

Conclusions

9.1 Summary

Though text based retrieval method is one of the most predominant formats of information

that is available on the Internet, other retrieval systems progress in their fundamental

technology and their facilities are quickly making other forms of multimedia more

practicable. Multimedia offers a great experience than in plain text, it appears as a more

widely user data format, it is significant to address the problems of metadata standards,

presentation, query matching and problem evaluation in order to ensure the growth and

distribution of effective and efficient multimedia information retrieval systems.

9.2 Limitations

There are few limitations in this project which can be rectified in the near future. Due to lack

of time the survey conducted to identify the problems faced in multimedia is analysed as a

whole, so we can understand the problems only in the intermediate level. In the future an in-

depth analysis can be made by conducting the survey separately on each media types (Audio,

Video and Images), so that it will be very effective in understanding the problems.

9.3 Future Directions

We believe that mobile multimedia will expand the uses of mobile phones. Phones are an

important medium for communication but it will also develop a wide variety of services. The

success of Multimedia depends on media such as television, radio and the Internet. Even

though there is progress in academic research of Multimedia Information Retrieval, there is

also some impact on MIR research into commercial applications with some exceptions such

as video segmentation. An example of merging academic and commercial application is

PicsMatch.com (http://www.picsmatch.com/).Their goal is to have a commercial product

that uses the academic research in face detection and recognition. Another example is the

Magic Video Browser (www.magicbot.com) which transfers MIR research in video

summarization to desktop computer and has a plug-in architecture for adding summarizing

methods as they appear in the research community. One of the long-term creativity is the

launch of Yahoo! Research Berkeley (research.yahoo.com/Berkeley), where new research

http://www.picsmatch.com/

http://www.magicbot.com/


62

collaboration is created between Yahoo! Inc. and UC Berkeley with the intention to invent

the social media and mobile media technology and their applications that enable people to

create, describe, find, share and remix media on the web. Nevenvision

(www.nevenvision.com) is one of the fast growing technologies for mobile phones that use

visual recognition algorithms in finding the latest technology. However, their efforts are just

in initial stage and we strongly believe that there is an opportunity in the growth of

multimedia search field (Battelle, 2005).

To assess research effectively in multimedia retrieval, their need of some task-related

standardized databases on which different groups can apply their algorithms. In text retrieval,

it has to obtain large collections of old newspaper text because the copyright owners will not

consider the raw text as valuable. However image, video and speech libraries have a great

value in their collections and are much more cautious in releasing their content. Although it

is not a research challenge, obtaining multimedia collection for evaluating benchmarking is

an important step that needs to be addressed. One possible solution is that task-related image

and video databases with appropriate relevance judgments are included and made available

to groups for research purposes as is it done with TRECVID (INRIA, 2010). Video

collections would include news video, personal videos and movie collections. Image

collections would include image databases along with annotated text (NIST, 2011).

Therefore, the cooperation between the private industry and academia is strongly fortified.

The key idea to be focused here is on efforts where both industry and academia is benefited

equally. As we renowned earlier, it is clear that industries should focus on information needs

of users in the retrieval of information, where the industry can contribute significantly in

understanding the information needs of users. Furthermore, by having a close relationship

with the industries we can clearly express our suggestions to improve towards increase in

user satisfaction.

The potential view of multimedia information retrieval is quite wide and diverse. Following

are some possible areas for additional MIR research challenges.

9.3.1 Human Centered Methods

The user has to be much focused, who may need to explore instead of search. It has been

stated that decision makers need to explore an area to acquire valuable vision, thus observed

system that signifies the exploration features that are encouraged. Studies on the user needs

on giving us understanding of their patterns and desires are also highly encouraged. New

http://www.nevenvision.com/


63

interactive devices should be tested to provide new possibilities, such as human emotional

state detection and tracking.

9.3.2 Multimedia Collaboration

As our world becomes more wired or wirelessly connected, the discovery of human-

computer-mediated interaction is essential. Multimodal collaboration environment hold over

many questions: How do people find each other? How does an individual discover

meetings/collaborations? What are the most effective multimedia interfaces in these

environments for different purposes, individuals, and groups? Multimodal processing has

many potential roles that ranges from transcribing and summarizing meetings to correlating

voices, names, and faces, to tracking individual (or group) attention and intention across

media.

Query model is the important one, which need benefit from collaboration environment. One

solution is to use an event-based query approach (Liu et al. 2004) which provides the users a

more feasible way to access the related media content with the domain knowledge provided

by the environment model. This approach would be extremely important when dealing with

live multimedia in which the information is occupied in a real-life setting by variety of

sensors.

9.3.3 No Solved Problems

From the most recent panel discussions at the major MIR scientific conferences including

ACM MIR and CIVR, it is agreed that there are no “solved” problems. The general problems

remain largely unsolved, which needs further research [ICMR, 2011].

Word Count – 15,138


64

Chapter: 10

References

American library association. [Online]. http://www.ala.org/ [Accessed 17 July 2011].

Angelides, M.C and Dustdar. S. (1997). Multimedia Information Systems. Boston: Kluwer.

Aslandogan, Y. A. and Yu, C. T. (1999). “Techniques and systems for image and video

retrieval”. Knowledge and Data Engineering, 11 (1), 56–63.

Attamah, M.K and Robert, C.A. (2010). “Segmented Multimedia document Access for

Knowledge Management”. The journal of information and knowledge management systems,

40 (1), 83-89.

Battelle, J. (2005). The Search: How Google and Its Rivals Rewrote the Rules of Business

and Transformed Our Culture. USA: Portfolio Hardcover.

Beaulieu, M. (2003). “Approaches to user-based studies in information seeking and retrieval:

a Sheffield perspective”. Journal of Information Science, 29 (4), 239-248.

Belkin, N.J. (1980), “Anomalous states of knowledge as a basis for information retrieval”.

Canadian Journal of Information Science, 5 (2), 133-43.

Browne, P. and Smeaton, A. F. (2004). “Video information retrieval using objects and

ostensive relevance feedback”. In SAC ’04: Proceedings of the 2004 ACM symposium on

Applied computing, 21 (5), 1084–1090.

Buijs, J. M. and Lew, M. S. (2003). “Visual learning of simple semantics in images cape”. In

Proceedings of the Third International Conference on Visual Information and Information

Systems, 4 (1), 7-34.

Byrd, D. and Crawford, T. (2002). “Problems of music retrieval in the real world”.

Information Processing and Management, 38 (2), 249-272.

Canuel, R and Crichton, C. (2011). “Canadian academic libraries and the mobile web”. New

library world, 112 (3-4), 107-120.

http://www.ala.org/


65

Carlsson, C. et al. (2005). “Adoption of Mobile Services across Technologies. In

Proceedings of the 18th Bled eConference, 37(8), 982-1002.

Carpineto, C. et al. (2009), “A survey of web clustering engines”, ACM Computing Surveys,

41 (3), 17-38.

Castells, M. (2001). The internet galaxy: Reflections on the internet, business and society.

New York: Oxford university press.

Chang, S. and Kunii, T. (1981). “Pictorial database systems”. IEEE Computer, 14 (11), 13–

21.

Chiu, C.K. and Lin, C.P. (2011). “Understanding helping intention and its antecedents

among instant messaging users”. Online Information Review, 35 (3), 386-400.

Cloete, L. (2009). “Multimedia Information storage and retrieval: Techniques and

Technologies”. Library Hi Tech, 27 (3), 484-485.

Corridoni, J. et al. (1999). “Image retrieval by color semantics”. Multimedia Systems, 7 (3),

175–183.

Coorough, C. (2001). Multimedia and the Web. Orlando: Harcourt, Inc.

Curwen, P and Whalley, J. (2011). “Mobile telecommunications gives birth to a fourth

generation: an analysis of technological”. Licensing and strategic implications. 13 (4), 42-60.

David, A. and Maghrebi, H. (2007), “Integrating user‟s needs into multimedia information

retrieval system”. Proceeding of 3rd International Conference on Computer Science

ATINER, Greece. 5 (2). http://hal.inria.fr/inria-00167511/fr/ [Accessed 20 August 2011].

Davies, R. (1989). “The creation of new knowledge by information retrieval and

classification”. Journal of documentation, 45 (4), 353-364.

Dimmick, J. et al. (2004). “Competition between the internet and traditional news

media: the gratification-opportunities niche dimension”. Journal of Media Economics,

17(1), 19-33.

http://hal.inria.fr/inria-00167511/fr/


66

Downie, J. (2003). “Music information retrieval”. Annual Review of Information Science

and Technology, 37(2), 295–340.

Efremidis, S. et al. (2011). “Experiences with G2G: a location-aware mobile social

networking system”. International journal of pervasive computing and communications, 7(2),

98-113.

Elliott, G. and Phillips, N. (2004). Mobile Commerce & Wireless Computing. New Jersey:

Addison-Wesley.

Fallows, D. (2004). Pew internet and American life project: The Internet and daily life.

[Online]. http://www.pewinternet.org/ [Accessed 19 July 2011].

Feldman, T. (1994). Multimedia. London: Blueprint.

Feng, D.D. et al. (2003). Multimedia information retrieval and management: technological

fundamentals and applications. New York: Springer

Garg, V. (2007). Wireless Communications & Networking. San Francisco: Morgan

Kaufmann.

Gaughan, G. et al. (2003). “Design, implementation and testing of interactive video retrieval

systems”. In MIR ’03: Proceedings of the 5th ACM SIGMM international workshop on

Multimedia information retrieval, 37 (7), 23–30.

Ghias, A. et al. (1995). “Query by humming: musical information retrieval in an audio

database”. In MULTIMEDIA ’95: Proceedings of the third ACM international conference on

Multimedia, 82 (6), 231–236.

Girgensohn, A. et al. (2005). “A synergistic approach to efficient interactive video retrieval”.

In INTERACT 2005, 40 (2), 781–794.

Gunsel, B.et al. (1998). “Temporal video segmentation using unsupervised clustering and

semantic object tracking”. Journal of Electronic Imaging, 7 (3), 592–604.

Hall, H. (2011). “Relationship and role transformations in social media environments”.

Electronic library, 29 (4), 236-241.

http://www.pewinternet.org/


67

Hashmi, M.A. and Guvenli, T. (2001). “Multimedia content on the web: the problem and

prospects”. Managerial Finance, 27 (7), 34-41.

Hawkins, D.T. (1983). Online Information Retrieval Bibliography 1964-82. Medford:

Information Today.

Hersh, W. (2009). Information Retrieval – A Health and Biomedical Perspective, 3rd ed.

New York: Springer.

Hider, P. (2006). “Search goal revision in models of information retrieval”. Journal of

Information Science, 32 (4), 352-361.

Hijikata, Y. K. et al. (2006). “Content-based music filtering system with editable user

profile”. In SAC ’06: Proceedings of the 2006 ACM symposium on applied computing, 17(3),

1050–1057.

ICMR. (2011). ACM International conference on Multimedia Retrieval. [Online].

http://www.icmr2011.org/ [Accessed 21 August 2011].

INRIA. (2010) .Evaluation and metrics for video understanding. [Online].

http://www.inria.fr/en/ [Accessed 21 August 2011].

International Telecommunications union. Internet users per 100 inhabitants 1997-2007

[Online].

http://upload.wikimedia.org/wikipedia/commons/thumb/2/25/Internet_users_per_100_inhabi

tants_1997-2007_ITU.png/300px-Internet_users_per_100_inhabitants_1997-2007_ITU.png

[Accessed 11 July 2011].

Internet and mobile association of India. [Online].

http://www.idra.it/garnetpapers/C06Sumanjeet_Singh.pdf [Accessed 11 July 2011].

I.R.I.S Working Group. [Online].https://www.dimis.fim.uni-

passau.de/iris/index.php?view=mpqf [Accessed 14 August 2011].

Jansen, B. J. et al. (2000).” Real life, real users, and real needs: A study and

analysis of user queries on the Web”. Information Process Management. 36(20), 207–227.

http://www.icmr2011.org/

http://www.inria.fr/en/

https://www.dimis.fim.uni-passau.de/iris/index.php?view=mpqf

https://www.dimis.fim.uni-passau.de/iris/index.php?view=mpqf


68

Jansen, B. J. & Spink, A. (2005). “An analysis of Web searching by European All

theWeb.com users”. Information Process Management. 41(2), 361–381.

Jarvelin, K. et al. (2001). “Document text characteristics affect the ranking of the most

relevant documents by expanded structured queries”. Journal of Documentation, 57 (3), 358-

376.

Kato, T. et al. (1992). “A sketch retrieval method for full color image database query by

visual example”. In Proceedings of the 11th IAPR International Conference on Computer

Vision and Applications, 89 (9), 530-533.

Kelly, D. and Fu, X. (2007). “Eliciting better information need descriptions from users of

information systems”. Information Processing and Management, 43 (1), 30-46.

Keshavarz, H. (2008). “Human information behaviour and design, development and

evaluation of information retrieval systems”. Program: electronic library and information

systems, 42 (4), 391-401.

Kim, Y. S. (2011). “Text recommender system using user's usage patterns”. Industrial

Management and data systems, 111 (2), 282-297.

Kopomaa, T. (2000). City in your pocket: Birth of the Mobile Information Society. Helsinki:

Gaudeamus.

Koskinen, I. et al. (2002). Mobile Image. Helsinki: Edita Ltd.

Kraft, D.E. and Bookstein, A. (1978). “Evaluation of information retrieval system: a decision

theory approach”. Journal of the American Society for Information Science, 29(1), 31-40.

Kuhlthau, C. (1991). “Information Access and Information needs”. Journal of the American

society for Information science, 42(5), 361-371.

Lake, S. E. and Bean, K. (2004). Multimedia and Image Management. Mason: Thomson

Southwestern.

Lew, M. S. et al. (2006). “Content-based multimedia information retrieval: State of the art

and challenges”. ACM Transactions on Multimedia, 2 (1), 1–19.


69

Li, Y. (1999). Semantic Multimedia information retrieval. [Online].

http://bscorpio.tripod.com/my/tenmonre.pdf [Accessed 3 August 2011].

Liu, H. et al. (2004). “Effective browsing of web image search results”. In

Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information

Retrieval, 2 (2), 174-180.

Lopez, J and Roman, R. (2009). “Integrating wireless sensor networks and the internet: A

security analysis”. Internet Research, 19(2), 246-259.

Maes, P. (1994). “Agents that reduce work and information overload”. Communications of

the ACM, 37(7), 31–40.

Manning, C.D. et al. (2009). Introduction to Information Retrieval. Cambridge: Cambridge

University Press.

Magalhaes, J.M.C. (2008). Statistical model for semantic multimedia information retrieval.

[Online]. http://people.kmi.open.ac.uk/stefan/www-pub/j.magalhaes-phd.pdf [Accessed 17

July 2011].

Marchionini, G. and Komlodi, A. (1998). Design of interfaces for information seeking.

Medford: Information Today.

Mass Registration. (2011). Multimedia Presentation Basics. [Online].

http://massregistration.com/category/it-web-communication-services/internet-multimedia-

services/ [Accessed 14 August 2011].

Mooers, C. N. (1951). “Zatocodiug applied to mechanical organization of knowledge”.

American Documentation, 28 (2), 20-32.

Naphide, H. and Huang, T. (2001). “A probabilistic framework for semantic video indexing,

filtering, and retrieval”. IEEE Transactions on Multimedia, 3 (1), 141–151.

National Consumer Research Centre in Finland. [Online].

http://www.kuluttajatutkimuskeskus.fi/en/ [Accessed 12 August 2011].

Natsev, A. et al. (2004). “Walrus: a similarity retrieval algorithm for image databases”. IEEE

Transactions on Knowledge and Data Engineering, 16 (3), 301–316.

http://bscorpio.tripod.com/my/tenmonre.pdf

http://people.kmi.open.ac.uk/stefan/www-pub/j.magalhaes-phd.pdf

http://massregistration.com/category/it-web-communication-services/internet-multimedia-services/

http://massregistration.com/category/it-web-communication-services/internet-multimedia-services/

http://www.kuluttajatutkimuskeskus.fi/en/


70

NIST. (2011). TREC Video Retrieval Evaluation Publications. [Online].

http://www.nist.gov/index.html [Accessed 21 August 2011].

Notess, G. (2000). Searching beyond text: Multimedia search Tools. [Online].

http://www.onlinemag.net/ol2000/net11.html [Accessed 14 August 2011].

Notess, G.R. (2006). Teaching web search skills: Techniques and strategies of top trainers.

New Jersey: Information today.

O'Callaghan, J. (2003). “Implementing wireless communications”. Sensor Review, 23 (2),

102-108.

Okazaki, S. and Romero, J. (2010). “Online media rivalry: A latent class model for mobile

and PC internet users”. Online information review, 34 (1), 98-114.

Pagani, M. (2004). “Determinants of Adoption of Third Generation Mobile Multimedia

Services”. Journal of Interactive Marketing, 18 (3), 46-59.

Peak Positions. (2011). Top search Engine Placement Company. [Online].

http://www.peakpositions.com/search-engine-placement.htm [Accessed 14 August 2011].

Pesch, D. (2008). Mobile Communication Systems and Networks. Finland: John Wiley and

Sons Ltd.

Pickens, J. et al. (2003).”Polyphonic score retrieval using polyphonic audio queries: A

harmonic modeling approach”. Journal of New Music Research, 31(4), 223 – 236.

Pickering, M.J. and Ruger, S. (2003). “Evaluation of key-frame based retrieval techniques

for video”. Computer Vision and Image Understanding, 92(2), 217-235.

Pok, S.H. and Teo, T.S.H. (2003). “Adoption of WAP-Enabled Mobile Phones among

Internet Users”. Omega, 31 (6), 483-498.

Prasanna, A. (2009). Mobile phone users by age group. [Online].

http://comm215.wetpaint.com/photo/4700954/Mobile+phone+Users+by+age+group

[Accessed 9 August 2011].

http://www.nist.gov/index.html

http://www.onlinemag.net/ol2000/net11.html

http://www.peakpositions.com/search-engine-placement.htm

http://comm215.wetpaint.com/photo/4700954/Mobile+phone+Users+by+age+group


71

Preez, M. D. (2004). “Multimedia Systems and Content-based Image Retrieval”. The

Electronic Library, 22 (3), 287-287.

Premkamolnetr, N. (2002). “Design Management of Multimedia Information Systems:

Opportunities, Challenges”. Online information Review, 26 (1), 57-66.

Prosyst. (2011). Mobile Media Server. [Online].

http://www.prosyst.com/index.php/de/html/content/65/Mobile-Media-Server/ [Accessed 3

August 2011].

Rackley, S. (2007). Wireless Networking Technology: From Principles to Successful

Implementation. Burlington: Newnes.

Rashmi .(2010). Brief history of multimedia. [Online].

http://churmura.com/technology/brief-history-of-multimedia/30271/ [Accessed 22 August

2011].

Robins, D. (2000). “Interactive information retrieval: context and basic notions”.

Information Science, special issue on Information Science Research, 3 (2), 57-62.

Rogers, E.M. (1995). Diffusion of Innovations. New York: The Free Press.

Rui, Y. et al. (1999).” Image retrieval: current techniques, promising directions and open

issues”. Journal of Visual Communication and Image Representation, 10 (1), 39–62.

Ruthven, I. (2008). “Interactive information Retrieval”. Review of Information Science and

Technology, 42 (1), 43-91.

Salton, G. and McGill, M.J. (1983). Introduction to Modern Information Retrieval. New

York: McGraw-Hill.

Schiller, J. (2003). Mobile Communications (2nd ed). New Jersey: Addison – Wesley.

Sebe, N. et al. (2003). “The state of the art in image and video retrieval”. In Image and Video

Retrieval, 13 (3), 152-162.

Shuman, J. (2002). Multimedia Concepts, Enhanced Edition—Illustrated Introductory.

Boston: Thomson Course Technology.

http://www.prosyst.com/index.php/de/html/content/65/Mobile-Media-Server/

http://churmura.com/technology/brief-history-of-multimedia/30271/


72

Sivic, J. and Zisserman, A. (2003). “Video Google: a text retrieval approach to object

matching in videos”. In Proceedings of the Ninth IEEE International Conference on

Computer Vision, 53(2), 169-191.

Smeaton, A.F. and Over, P. (2003). Benchmarking the Effectiveness of Information Retrieval

Tasks on Digital Video. London: Springer.

Smeulders, A. W. M. et al. (2000). “Content-based image retrieval at the end of the early

years”. IEEE Transactions on Multimedia, 22 (12), 1349–1380.

Snoek, C. G. et al. (2004). “The media mill TRECVID 2004 semantic video search engine”.

In Proceedings of the 2th TRECVID Workshop, 19 (5), 733-746.

Solomon, A.W. (2004). Introduction to Multimedia. Woodland Hills: Glencoe/McGraw- Hill

Sonera Media lab. (2002). Multimedia search engines white paper. [Online].

http://www.medialab.sonera.fi/search/query.cgi?query=search+engines [Accessed 10 July

2011].

Stallings, W. (2004).Wireless Communications and Networks (2nd ed). Arizona state:

Prentice Hall.

Stein, R.M. (1991). “Browsing Through Terabytes”. Byte, 16(5), 157-164.

Sullivan, D. (2003). Multimedia Search engines: Image, Audio and Video Searching.

[Online].

http://searchenginewatch.com/article/2066693/Multimedia-SearchEngines-Image-Audio-

Video-Searching [Accessed 29 July 2011].

Tieu, K. and Viola, P. (2004). “ Boosting image retrieval”. International Journal of

Computer Vision, 56 (1-2), 17–36.

Vakkari, P. and Jarvelin, K. (2005), “Explanation in information seeking and retrieval”.

Netherlands: Springer.

Vaughan, T. (2001). Multimedia: Making it Work (5th ed.). Berkley: Osborne/McGraw- Hill.

http://www.medialab.sonera.fi/search/query.cgi?query=search+engines

http://searchenginewatch.com/article/2066693/Multimedia-SearchEngines-Image-Audio-Video-Searching

http://searchenginewatch.com/article/2066693/Multimedia-SearchEngines-Image-Audio-Video-Searching


73

Vickery, B. (2002). “A history of information storage and retrieval”. Electronic Library and

Information Systems, 36 (4), 285-287.

Wactlar, H. D.et al. (1999). “Lessons learned from building a terabyte digital video library”.

Computer, 32 (2), 66–73.

Walker, P. (2000). “The Dictionary of Multimedia: Terms and Acronyms 1999 edition”.

Reference Reviews, 14 (2), 30-31.

Wilson, T.D. (1981). “On user studies and information needs”. Journal of Documentation,

37 (1), 3-15.

Wilson, T. (1999), „„Models in information behaviour research‟‟. Journal of documentation,

55(3), 249-269.

Yan, R. et al. (2003). “Negative pseudo-relevance feedback in content-based video retrieval”.

In MULTIMEDIA ’03: Proceedings of the eleventh ACM international conference on

Multimedia, 13 (2), 343– 346.

Yan, R. and Hauptman, A. (2005). “Co-retrieval: a boosted re-ranking approach for video

retrieval”. Vision, Image and Signal Processing, 152 (6), 888– 895.

Yon, J. (2008). “Searching for image conveying connotative meanings: an exploratory cross-

cultural study”. Library and information science Research, 30 (4), 312-318.

Yu, K. (2004). Statistical Learning Approaches to Information Filtering. Munich:

Dissertation.

Zhang, H.et al. (1993). “Automatic partitioning of full-motion video”. Multimedia Systems, 1

(1), 10–28.


74

Chapter: 11

Appendix

Appendix A: Screen Shots of Yahoo! Appendix A-1: Yahoo! Image Search engine

Here I have attempted to find the Images with keyword Sheffield and the information related

to those keywords are resulted.

Appendix A-2: Yahoo! Video Search engine

Here I have attempted to find the Video with keyword Manchester United and the

information related to those keywords are resulted.


75

Appendix B: Screen Shots of LYCOS Appendix B-1: LYCOS Image Search engine

Here I have attempted to find the Images with Keyword University of Sheffield and the

information related to those keywords are resulted.

Appendix B-2: LYCOS Video Search engine

Here I have attempted to find the Video with keyword Apple I phone 4 and the information

related to those keywords are resulted.


76

Appendix C: Participants Background and Knowledge

This survey was conducted to know the Participants Background and Knowledge.

1. What is your Age?

20-21 22-23 24-25 26-27

2. Have you used any multimedia search engines before?

yes no

3. How often you use internet from your mobile?

Daily Weekly Once in a week Twice in a week Several

times

4. How do you rate yourself in using web based search engines?

Beginner Intermediate Expertise

5. How often do you use web based search engines?

Daily Weekly Once in a week Twice in a week Several

times

6. Describe your Education level?


77

Appendix D: Survey Questionnaire

Survey questions sent to Participants to analyse the Problems faced by Mobile Multimedia

users.

This Survey Questions is sent to exactly 40 participants between the age group of 20 -27 and

the participants are targeted from different countries including UK, China, India and Nigeria.

This Survey is conducted through Survey Monkey (Online Survey tool).

1. What is the make of your Mobile Phone?

Nokia Samsung Sony Ericsson LG Apple HTC

Blackberry

2. Which design features do you rate highly for Mobile Phones?

Weight Size Operating System Appearance Entertainment

Ease-of-use Functionality Memory Processor Speed

3. Which Multimedia Search Engine(s) have you used in your phone?

Google Yahoo Bing Lycos Alta Vista AllTheWeb

4. Which website you think is the best for viewing/downloading images?

Picasa Flickr Image shack Photo Bucket Tiny pic

5. Which website is the best for watching/downloading videos?

YouTube Metacafe Daily motion Vimeo Blip.tv


78

6. Which website you think is the best for Listening/Downloading Music?

MusOpen Pandora Raaga Grooveshark Uwall classical

7. Which causes more problems when handling multimedia content in your

mobile phone?

Mobile OS Browsers Display resolution User input

8. Which factors affect you most when using multimedia apps in your mobile

phone?

Battery Over-heating Reduce in speed Incompatible data

Screen size

9. Which feature do you use mostly in your mobile phone?

MMS Photo Capture Video Recording Music Navigation

Social Networking

10. In your perspective, what make a good mobile-friendly website?

Compatability Optimised content Usability Design

Navigation

11. Which device do you recommend for browsing webpage?

Mobile Phone Tablet PC Net book


79

12. In the future do you think mobile phones can handle multimedia content as

efficiently as a PC?

yes No

13. Which video data type is the least compatible in your mobile phone?

3gp Mov Avi Mkv MP4

14. Which audio data type is the least compatible in your mobile phone?

MP3 WMV WAV AIFF

15. Which image data type is least compatible in your mobile phone?

JPEG GIF TIFF PNG BMP

16. Which features is must-have in your future mobile phone?


80

Appendix E: Summary of Survey Results Conducted with

Appendix D (Questionnaire).

Q.1: 1. what is the make of your Mobile Phone?

Q.2: Which design features do you rate highly for Mobile Phones?

Make of Mobile Phone

Nokia

Samsung

Sony Ericssion

LG

Apple

HTC

Blackberry

Design Features

Weight

size

Operating System

Appearance

Entertainment

Ease of use

Functionality

Memory

Processor Speed


81

Q.3: Which Multimedia Search Engine(s) have you used in your phone?

Q.4: Which website you think is the best for viewing/downloading images?

Search Engines

Google

yahoo

Bing

Lycos

AllTheWeb

AltaVista

Viewing/Downloading Images

Picasa

Flickr

ImageShack

PhotoBucket

Tiny Pic


82

Q.5: Which website is the best for watching/downloading videos?

Q.6: Which website you think is the best for Listening/Downloading Music?

Watching/Downloading Videos

Youtube

Metacafe

Dailymotion

Vimeo

Blip.tv

Listening/Downloading Music

Musopen

Pandora

Raaga

Grooveshark

UwallClassic


83

Q.7: Which causes more problems when handling multimedia content in your

mobile phone?

Q.8: Which factors affect you most when using multimedia apps in your mobile

phone?

Problems in Handling Multimedia Content

Mobile OS

Browsers

Display Resolution

User Input

Factors affect Multimedia Apps

Battery

Over Heating

Reduce in Speed

Incompatible Data

Screen Size


84

Q.9: Which feature do you use mostly in your mobile phone?

Q.10: In your perspective, what make a good mobile-friendly website?

Features Mostly Used

MMS

Photo Capture

Video recording

Music

Social Networking

Navigation

Good Mobile Friendly website

Compatibility

Optimised Content

Usability

Design

Navigation


85

Q.11: Which device do you recommend for browsing webpage?

Q.12: In the future do you think mobile phones can handle multimedia content

as efficiently as a PC?

Device Recommended

Mobile Phone

Tablet

PC

NetBook

Sales

Yes

No


86

Q.13: Which video data type is the least compatible in your mobile phone?

Q.14: Which audio data type is the least compatible in your mobile phone?

Least Compatible Video Datatype

3GP

Mov

MKV

MP4

Reality Motion

Least Compatible Audio datatype

MP3

WMV

WAV

AIFF


87

Q: 15: Which image data type is least compatible in your mobile phone?

Least Compatible Image datatype

JPEG

GIF

TIFF

PNG

BNP

Documents

Mobile Multimedia Information Retrievaldagda.shef.ac.uk/dispub/dissertations/2010-11/External/VSunder_Su… · Mobile Multimedia Information retrieval 2011 3 Contents Chapter 1: Introduction