Web- and Multimedia-based Information Systems

Assessment

Presentation Programming Assignment

Presentations

Document Management Systems & OCR– Market Overview– Algorithm Introduction

Video on Demand– Real Media– Technology

Authoring Systems– Macromedia Products

Presentations

Content Management– Functionality– Market Overview– Opencms

Application Server– Functionality– Market Overview

Presentations

VRML– Syntax Introduction– Exercise

SMIL : Multimedia Synchronisation– Syntax Introduction– Exercise

Presentations

Software / Frontend Ergonomics (HCI)

Usability Navigation

What are Information Systems?

Store Information Retrieval

Information

Textual Audiovisual

– Images– Audio– Video

Multimedia Documents

Information System Classification

Expert Systems Transaction Processing Systems Office Automation Systems Management/Executive Information Systems Geographic Information Systems Information Retrieval Systems

Expert Systems

Problem Solving Artificial Intelligence Replace an Expert Multiple operational Implementations Often Implemented using Prolog

Transaction Processing Systems

Records Events of interest to an organization Supports the operational level of the

business High data volume

TPS applications

Manufactoring and Production Sales and Marketing Finance and Accounting Human Resources

Office Automation

Personal Productivity Groupware & Communications

Management/Executive Information Systems

Analysis of TPS data Higher Level Reports Drill Down to detailed Information possible

Geographic Information Systems

Different Sources Spatial Data Visualization

Information Retrieval

Information Retrieval System

Manages Documents = Records of Information

Presents relevant Documents on a Query

Information Retrieval System Examples

POTS directory assistance Library Catalog World Wide Web Search Engine

Information Retrieval

Deals with the– Representation of– Storage of– Organization of– Access to

Information items

History

Early Example: Book‘s Table of Contents Indices in libraries Only recently automatic indexing The Web

– Easy & cheap access– Variety of sources– Freedom of Publication, Interactivity

Data Retrieval vs Information Retrieval

Exact match Looks for matching

items Complete Query Data with well defined

structure and semantics

Best match Looks for Relevant

Items Incomplete Query Natural Language

Documents

Information Retrieval and the Web

IR originally Text Indexing and Searching Web is highly heterogenous System, no

common data model Navigation is ineffiecient Information Retrieval promises to structure

information and ease fulfilling information needs

Usage: Information Retrieval

User has Information need User translates this need into a machine-

understandable Query System retrieves relevant Information

The User

Retrieval

Browsing

Database

Logical Views of a Document

Full text Set of Index Terms

– Specified by human expert– Text Operations

Elimination of Stopwords Stemming Compression

Intermediate Logical Views Structure Recognition

Retrieval Process

User Interface

Text Operations

Text Database

DB Manager Module

Index

Searching

Ranking

Operational Modes

Ad Hoc– Fixed Database, changing Queries

Filtering– Fixed Queries, changing Database– User Profiles

Information Retrieval Data Structures

Data Structures

Linear list Sequentially ordered file Indexed file

Linear List

Unsorted list of documents Easy addition of files Traversal required for a search

AuthorD

AuthorE

AuthorA

AuthorF

1 2 3 4 5 6 7

AuthorB

AuthorG

AuthorC

Sequentially Ordered File

Sorted by the values of a Key Addition of documents more involved Binary search possible

AuthorA

AuthorB

AuthorC

AuthorD

1 2 3 4 5 6 7

AuthorE

AuthorF

AuthorG

Indices

A 1

B 2

.

.

.

F 6

AuthorA

AuthorB

AuthorC

AuthorD

1 2 3 4 5 6

AuthorE

AuthorF

Inverted Indices

An index of all the words in the texts Vocabulary

– Different Words in the text– Little Space required after Text Operations

Occurences– Positions– More Space required, ~30-40% of text size

Inverted Indices

Block Addressing– Smaller Pointers– References in one block are collapsed– Online Search required for exact positions– Fixed Size Blocks or Natural Cuts

Fully Inverted Indices– For less readily accessable collections if exact

position is required

Information Retrieval Models

Classic IR Models

Boolean Vector Probabilistic

Common Concepts

Index Terms Weigths for varying relevance

Boolean Model

Pro Easy to understand Precise Semantics of a query

Contra Binary Decision Difficult for users

Boolean Model

Example Query

Q = 1 AND ( 2 OR NOT 3)

AND

1 OR

2 NOT 3

Boolean Model – Set Operations

AND : Intersection (Durchschnitt) OR : Union (Vereinigung) NOT : Complement (Komplement)

– Seldom used on its own