Building an Intelligent Web

The World Wide Web has become an extremely popular way of publishing and distributing electronic resources. Though the Web is rich with information, collecting and making sense of this data is difficult because it is rather unorganized. Building an Intelligent Web introduces students and professionals to the state-of-the art development of Web Intelligence techniques and teaches how to apply these techniques to develop the next generation of intelligent Web sites. Each chapter contains theoretical bases, which are also illustrated with the help of simple numeric examples, followed by practical implementation. Students will find Building an Intelligent Web to be an active and exciting introduction to advanced Web mining topics. Topics covered include Web Intelligence, Information Retrieval, Semantic Web, Classification and Association Rules, SQL, Database Theory, Applications to e-commerce and Bioinformatics, Clustering, Modeling Web Topology, and much more!

Introduction to Web lntelligence	p. 1
Historical Perspective	p. 1
Toward an Intelligent Web	p. 1
Information Retrieval	p. 3
Semantic Web	p. 5
Knowledge	p. 6
Data Mining Applied to the Web	p. 6
Web Mining	p. 6
Web-Usage Mining	p. 8
Web-Content Mining	p. 9
Web-Structure Mining	p. 10
Building Better Web Sites Using Intelligent Technologies	p. 10
Benefits of Intelligent Web	p. 11
Guide to Using the Book	p. 12
What Is on the CD?	p. 13
Information Retrieval	p. 19
Introduction	p. 19
Document Representation	p. 20
Stemming	p. 24
Term-Document Matrix	p. 31
Standard Document Collections	p. 37
Linguistic Model for Document Representation	p. 44
Handling HTML and Other Document Formats	p. 44
Retrieval Models	p. 45
The Boolean Retrieval Model	p. 45
The Vector Space Model	p. 47
Variations of the VSM	p. 58
Probabilistic Information Retrieval	p. 60
Evaluation of Retrieval Performance	p. 62
Precision and Recall	p. 62
Other Performance Measures	p. 63
Public Domain Information Retrieval Systems	p. 66
Semantic Web	p. 11
Introduction	p. 71
The Layered-Language Model	p. 73
Metadata and Ontologies	p. 77
Explicit Metadata	p. 77
Ontologies	p. 79
Ontology Languages for the Web	p. 82
Extensible Markup Language (XML)	p. 83
Resource Description Framework	p. 102
XMLTopic Map	p. 109
Issues That May Affect the Development or Semantic Web	p. 115
Classification and Association	p. 119
Introduction	p. 119
Data Preparation	p. 119
Database Theory	p. 119
SQL	p. 124
An E-Commerce Database	p. 128
Classification	p. 138
ID3 Algorithm	p. 139
Rough Set Theory	p. 149
Classification Software CtreeinExcel	p. 151
Classifying Customers from Gazelle.com Using CtreeinExcel	p. 158
Association	p. 162
a priori Algorithm	p. 163
Demonstration for an E-Commerce Application	p. 169
Clustering	p. 177
Introduction	p. 177
Statistical Methods	p. 178
The k-Means Algorithm	p. 179
Other Methods	p. 187
Neural-Network-Based Approaches	p. 189
Kohonen's Self-Organizing Maps	p. 191
Other Neural-Network-Based Approaches	p. 197
Evolutionary Computing	p. 198
Application of Clustering to all E-Commerce Application	p. 199
Text Clustering	p. 200
Web Usage Mining	p. 205
Introduction to Web Mining	p. 205
Introduction to Web-Usage Mining	p. 206
Web-Log Processing	p. 206
Format of Web Logs	p. 207
Web-Access Logs: Apache-Server Example	p. 211
Analyzing Web Logs	p. 212
Summarization of Web-Access Logs	p. 212
Analysis of Clickstream: Studying Navigation Paths	p. 227
Visualizing Individual User Sessions	p. 232
Caution in Interpreting Web-Access Logs	p. 237
Web-Usage Mining Applications	p. 239
Clustering of Web Users	p. 239
Classification Modeling of Web Users	p. 248
Association Mining of Web Usage	p. 252
Sequence-Pattern Analysis of Web Logs	p. 254
Concluding Remarks	p. 259
Web Content Mining	p. 263
Introduction	p. 263
Data Collection	p. 263
Web Crawlers	p. 263
Implementation of a Web Crawler	p. 265
Multiple-Layered Database	p. 272
Search Engines	p. 273
Introduction to Search Engines	p. 273
Query Types	p. 275
Robot Exclusion	p. 277
Robots Exclusion Protocol	p. 278
Robots META Tag	p. 281
Personalization of Web Content	p. 282
Multimedia Information Retrieval	p. 282
Demonstration of a Multimedia Information Retrieval System	p. 284
Web Structure Mining	p. 289
Introduction	p. 289
Modeling Web Topology	p. 290
PageRank Algorithm	p. 294
Hyperlink-Induced Topic Search (HITS)	p. 306
Comparison of PageRank and HITS	p. 314
Random Walks on the Web	p. 315
Other Approaches to Studying the Web-Link Structure	p. 318
Social Networks	p. 318
Reference and Index Pages	p. 320
Index	p. 326
Table of Contents provided by Blackwell. All Rights Reserved.

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Building an Intelligent Web

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