World Wide WebPresented By

Bharath

Praveen

Swathi

World Wide Web

The World Wide Web was created in 1989 by Tim Berners-Lee, working at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland and released in 1992

Web - Accessing information over internet

It is not Internet – Network of networksEmail (SMTP), File sharing (FTP)

System of interlinked documents

Browser / Web Browser

The first Web browser, written by Tim Berners Lee and introduced in early 1991 ran on NeXT

Architecture

URI, URN & URL

<URI> := <scheme> : <scheme-specific-part>

Difference between URL, URN, and URI: URL: http://www.tmrf.org/kpr/issue1.htm

URN: www.tmrf.org/kpr/issue1.htm#one

URI: http://www.tmrf.org/kpr/issue1.htm#one

Web Protocols

ARP: Address Resolution ProtocolDHCP: Dynamic Host Configuration ProtocolDNS: Domain Name ServiceDSN: Data Source NameFTP: File Transfer ProtocolHTTP: Hypertext Transfer ProtocolIMAP: Internet Message Access ProtocolICMP: Internet Control Message ProtocolIDRP: ICMP Router-Discovery ProtocolIP: Internet ProtocolIRC: Internet Relay Chat ProtocolPOP3: Post Office Protocol version 3PAR: Positive Acknowledgment and RetransmissionRLOGIN: Remote LoginSMTP: Simple Mail Transfer ProtocolSSL: Secure Sockets LayerSSH: Secure ShellTCP: Transmission Control ProtocolTELNET: TCP/IP Terminal Emulation ProtocolUPD: User Datagram ProtocolUPS: Uninterruptible Power Supply

HTTP Hyper Text Transfer Protocol

HTTP 1.1 Persistent connections

Pipelining

Cache validation commands

Request Types: GET, POST, PUT, HEAD, DELETE, TRACE, OPTIONS, CONNECT

Request & Response

RequestGET

POST

Languages used

Client SideHTML, CSS, Javascript, AJAX, Flex3

Server Side.NET (Asp.net, VB.net, c#.net)Java (JSP, Servlets, Plain java class) CGI Perl / PHP

Other LanguagesAda 95, Applescript, BEF & Dylan (similar to PASCAL), CCI (Common Client Interface) , CMM, Guile, Hypertalk, Icon, KQML (Knowledge Query and Manipulation language), Linda, Lingo, Lisp, ML, Modula 3, Obliq, Phantom, Python, ReXX, ScriptX, SDI (Software Development Interface),VRML

Web 2.0

AJAXReverse AJAX

Democracy (Wiki, reddit, digg, youtube)

RIASOAMashupsWidgetsFeeds, RSS, Web servicesBloggingTagging

Ajax

Architecture

Ajax

Technologies AssociatedXHTML & CSS for presentationDOM to interact with dataXML & XSLT for interchange and manipulation of dataXMLHttpRequest object for asynchronous communicationJavascript to integrate all the above technologies

AdvantagesFast, No reload, updates the section of a page

• Disadvantages• Actions are not registered with browser’s history• Need an alternate way to be indexed• JavaScript must be enabled on the browser• Server load

Reverse AJAX

Server pushes data to all alive clientsDWR Direct Web Remoting

Mashups

Mixing multiple service together to produce newTypes: Data & Enterprise mashupsTools: Microsoft Popfly, Yahoo Pipes, Google Mashup editor

Widgets

UWA Universal Widget API from NetVibes

Feeds – RSS, JSON, Atom

Web 3.0

The Data Web making data as openly accessible and linkable as Web pages

Querying for data across distributed RDF databases

Semantic web

Open Social

A common API for social applications across multiple websitesSupports interoperability with other social networks that support themCore Services: People & Friends, Activities, PersistencePlatforms: google, hi5, myspace, ImeemHTML, JavaScript, REST, OAUTH

Summary

Making the web more socialCurrent version 0.7Orkut, MySpace, hi5, Netlog, Imeem, LinkedinEasy to get dataApache Shindig: to host open source applications

Semantic Web

IntroductionHistoryArchitectureChallengesFutureConclusion

Logo of Semantic Web

What is Semantic Web ?

Meaningful representation of data on World Wide Web

Processed by humans as well as machines in global scale

Why do we need Semantic Web ?

Enhanced Search and Discovery

Enhanced System and Data Interoperability

Knowledge Management

Semantic Web Service

Electronic Commerce

History

1989 – Vision of Tim-Berners Lee

1994 – Presented at first WWW conference

2002 – Architecture

Architecture

Source: Lee, T. B. Semantic Web - XML2000 – Architecture. Retrieved July 11, 2008 from http://www.w3.org/2000/Talks/1206-xml2k-tbl/slide10-0.html

Unicode and URI

Unicode – International standard for encoding textEx: UTF-8, UTF-16

URI – Universal Resource IdentifierUniform Resource Locator (URL)

Identify resources via a representation of their primary access mechanism

Ex: http://seal.ifi.unizh.ch

Universal Resource Name (URN)Globally unique and persistent even when the resource ceases to exist or becomes unavailable.

Ex: urn:ISBN:0-395-36341-1

XML and Namespace

eXtensible Markup LanguageStores data in related entitiesProvides standard for storage layout and logical structureSupports syntactic interoperability

NamespaceElements and attributes have expanded namesExpanded name = Namespace name + Local nameNamespace name – name holding URI

XML Schema

RDF – Resource Description Framework

Language for representing metadata of web resources

Framework for exchange of information between applications without loss of meaning

RDF Model

Resource - Thing being described by RDF expressionProperty - Specific aspect, characteristic, attribute, or relation used to describe a resource. Statement - A specific resource + a named property + the value of that property for that resource

Represented as 3-tuple – Subject, Predicate and ObjectEx: http://www.example.org/index.html has a creator called John Smith

RDF Model - Example

Source: Manola, Miller, McBride (2004, February). The RDF Primer. W3C Recommendations.

RDF Model – Example (Contd…)

Source: Manola, Miller, McBride (2004, February). The RDF Primer. W3C Recommendations.

Why RDF and not just XML ?

Many XML trees for single 3-tuple

XML parser cannot distinguish subject, object and property

RDF model – direct, unambiguous and decentralized

Why RDF and not just XML ? (Contd…)

Example3-tuple (index.html, John Smith, author)

Relationship: Index.html has author John Smith<?xml version="1.0"?>

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf- syntax-ns#" xmlns:exterms="http://www.example.org/terms/">

<rdf:Description rdf:about="http://www.example.org/index.html"> <exterms:creator>John Smith</exterms:creator> </rdf:Description>

</rdf:RDF>

Why RDF and not just XML ? (Contd…)

Possible XML trees<author>

<uri> Index.html </uri> <name>John Smith</name> </author>

<document href=" Index.html "> <author> John Smith </author> </document>

<document> <details> <uri>href=" Index.html "</uri> <author> <name> John Smith </name> </author> </details> </document> or maybe

<document> <author> <uri>href=" Index.html "</uri> <details> <name> John Smith </name> </details> </author> </document>

RDF Schema (RDFS)

Collection of classes authored for specific purpose or domain

Classes organized in hierarchy

Describes inheritance hierarchies, class schemas, properties, domain and range and restriction for properties

Supports extensibility and reusability

Multiple views of same metadata

RDFS - Example

<Class ID=“Animal”>

<Class ID="Male"> <subclass Ofresource="#Animal"/> </Class>  <Class ID="Female"> <subclass Ofresource="#Animal"/> <disjointFrom resource="#Male"/> </Class>

Web Ontology Language (OWL)

Extends from RDFS

Specifies axioms based on the classes of entities, their properties and relationships

Draw inference based on axioms

OWL (Contd…)

Source: Lee, T. B. Semantic Web Road map. Retrieved July 11, 2008 from http://www.w3.org/DesignIssues/Semantic.html

Challenges

Standardizing Semantic Web Stack

Developing Ontologies

Converting existing WWW into Semantic Web

Capturing Cultural Semantics

Interoperability Issues

Some News…

SPARQL Protocol

Semantic Search Engines – Google, Yahoo, Intelliseek

Jena Semantic Web Toolkit – HP

Joseki Web API – HP

Wilbur – Nokia

What is Cloud Computing?

An emerging computing paradigm where data and services reside in massively scalable data centers and can be ubiquitously accessed from any connected devices over the internet.

4+ billion phones by 2010 [Source: Nokia]

Web 2.0-enabled PCs,

TVs, etc.

Characteristics of Cloud Computing

Virtual – Physical location and underlying infrastructure details are transparent to users

Scalable – Able to break complex workloads into pieces to be served across an incrementally expandable infrastructure

Efficient – Services Oriented Architecture for dynamic provisioning of shared compute resources

Flexible – Can serve a variety of workload types – both consumer and commercial

Cloud Computing Building Blocks A massively scalable and flexible computing platform of the future,

built on IBM and open source software, for hosting Web 2.0 and SOA applications.

Business Benefits

• Cost efficient model for creating

and acquiring information services• Removes or reduces IT management

complexity• Increases business responsiveness

with real-time capacity reallocation• Powers rich internet applications

Enabling TechnologiesOpen source Linux platform

Xen open source systems virtualization

Automated provisioning of computing resources by Tivoli Provisioning Manager

Systems management and monitoring by IBM Tivoli Monitoring

Parallel computing clusters using Apache Hadoop

Open source Eclipse-based development tools for parallel applications

Cloud Computing Architecture

IBM Monitoring v.6

DB2

Provisioning Management Stack

Provisioning Manager v.5.1

WebSphere Application Server

Monitoring Provisioning Baremetal & Xen VM

Open Source Linux with Xen

Tivoli Monitoring Agent

Virtualized Infrastructure based on Open Source Linux & Xen

VirtualMachine

VirtualMachine

VirtualMachine

VirtualMachine

Data Center – System x

Apache

Examples of Cloud Computing Workloads

Web 2.0 applications

Software to scan voluminous Wikipedia edits to identify spam

Organize global news articles by geographic location

Data-intensive workloads based on scalable architectures.

Next generation rich media, such as virtual worlds, streaming videos, etc.

New services can be created and published via a completely integrated Eclipse-based environment

Joint IBM Google Announcement

IBM Almaden Research

Universities participating in initial pilot

Train future workforce with next generation computing skills

University initiative to promote open standards and emerging parallel computing model

Jointly provide compute platform of the future including hardware, software, and services to support new parallel computing curricula

Three active “clouds”

Google

U. Of Washington

Web Mining

Web mining is the use of data mining techniques to automatically discover and extract information from Web documents/services

Why is Web Information Retrieval Important?

Research

Health/Medicine

Travel

Business

Entertainment

Arts

Why is Web Information Retrieval Difficult?

The Abundance Problem

Hundreds of irrelevant documents returned in response to a search

query.

Limited Coverage of the Web

Largest crawlers cover less than 18% of Web pages

The Web is extremely dynamic

Lots of pages added, removed and changed every day

Very high dimensionality (thousands of dimensions)

Limited query interface based on keyword-oriented search

Limited customization to individual users

Web Mining Taxonomy

Web Mining

Web Usage Mining

Web Structure Mining

Web Content Mining

Web Mining Taxonomy

Web content mining: focuses on techniques for assisting a user in finding documents that meet a certain criterion (text mining)

Web structure mining: aims at developing techniques to take advantage of the collective judgment of web page quality which is available in the form of hyperlinks

Web usage mining: focuses on techniques to study the user behavior when navigating the web (also known as Web log mining and clickstream analysis)

Web Content Mining

Can be thought of as extending the work performed by basic search engines.

Search engines have crawlers to search the web and gather information, indexing techniques to store the information, and query processing support to provide information to the users

Web Content Mining is: the process of extracting knowledge from web contents

Semi-Structured Data

Content is, in general, semi-structured

Example:

Title

Author Publication_Date Structured attribute/value pairs

Length

Category

Abstract Unstructured

Content

Text Mining

Document classification

Document clustering

Key-word based association rules

Web Structure Mining

Early days: keyword based searches

Keywords: “web mining”

Retrieves documents with “web” and mining”

Later on: cope with

Synonymy problem

Polysemy problem

stop words

Modern search engines use link structure as

important source of information

Central Question:

Which useful information can be derived

from the link structure of the web?

Some Answers

1. Structure of Internet

2. Google

3. HITS: Hubs and Authorities

General Structure of the Web

Google

Search engine that uses link structure to calculate a quality ranking (PageRank) for each page

Intuition: PageRank can be seen as the probability that a “random surfer” visits a page

Keywords CMPE272 entered by user

Select pages containing CMPE272 and pages which have in-links with caption CMPE272.

Font sizes of words in text: Words in larger or bolder font are assigned higher weights.

HITS (hyperlink-Induced Topic Search)

HITS uses hyperlink structure to identify authoritative Web sources for broad-topic information discovery

Premise: Sufficiently broad topics contain communities consisting of two types of hyperlinked pages:

Authorities: highly-referenced pages on a topic

Hubs: pages that “point” to authorities

A good authority is pointed to by many good hubs; a good hub points to many good authorities

Hubs and Authorities

Hub pages point to interesting links to authorities = relevant pages

Authorities are targets of hub pages

Web Usage Mining

Pages contain information

Links are “roads”

How do people navigate over the Internet?

⇒Web usage mining (Clickstream Analysis)

Information on navigation paths are logged.

Web Usage Analysis

Data Sources

Web Usage Mining Process

Data Preparation

Data cleaning

By checking the suffix of the URL name, for example, all log

entries with filename suffixes such as, gif, jpeg, etc

User identification

If a page is requested that is not directly linked to the

previous pages, multiple users are assumed to exist on the

same machine

Other heuristics involve using a combination of IP address,

machine name, browser agent, and temporal information to

identify users

Transaction identification

All of the page references made by a user during a single visit

to a site

Size of a transaction can range from a single page reference to

all of the page references

References - Web

Bryan Basham, Kathy Sierra, & Bert Bates. (2008). Head first servlets and JSP Oreilly & Associates Inc.

Dan Harkey, Robert Orfali, & Jeri Edwards. Client/Server survival guide (Third ed.) Wiley.

Open social. (2008). http://www.opensocial.org/

Praveen, A. (2008). Job quest mashup.http://praveen.987mb.com/Projects/JobDashBoard/HTML/JobQuest.html

Wikipedia. (2008). http://en.wikipedia.org/wiki/Main_Page

References – Semantic Web

Lee, T. B. (1998, September). Semantic Web Road map. Retrieved July 11, 2008 from http://www.w3.org/DesignIssues/Semantic.htmlLee, T. B. Semantic Web - XML2000. Retrieved July 11, 2008 from http://www.w3.org/2000/Talks/1206-xml2k-tbl/Overview.htmlManola, Miller, McBride (2004, February). The RDF Primer. W3C Recommendations.Lee, T. B. (1998, September). Why RDF model is different from the XML model. Retrieved July 11, 2008 from http://www.w3.org/DesignIssues/RDF-XML.htmlW3C. (1999, January). Resource Description Framework(RDF) Model and Syntax Specification. Retrieved July 11, 2008 from http://www.w3.org/TR/PR-rdf-syntax/Palmer, S., B. (1999, September). The Semantic Web: An introduction. Retrieved July 11, 2008 from http://infomesh.net/2001/swintro/#itWorks

References

www.umass.edu/research/rld/iln/uploads/Cloud%20Computing%20Oct%2003%20Ext.ppt

en.wikipedia.org/wiki/Cloud_computing

infolab.stanford.edu/~ullman/mining/2006/lectureslides/web%20mining%20overview.pdf

www.cs.uic.edu/~liub/WebContentMining.html

en.wikipedia.org/wiki/Web_mining