Modeling the Internet and the Web
Probabilistic Methods and Algorithms
1st Edition
Published on 25. April 2003
Book
Hardback
306 pages
978-0-470-84906-4 (ISBN)
Description
Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.
* Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.
* Takes a modern approach based on mathematical, probabilistic, and graphical modeling.
* Provides an integrated presentation of theory, examples, exercises and applications.
* Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web.
Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business, and the social sciences.
"This book is fascinating!" - David Hand (Imperial College, UK)
"This book provides an extremely useful introduction to the intellectually stimulating problems of data mining electronic business." - Andreas S. Weigend (Chief Scientist, Amazon.com)
Reviews / Votes
"...I congratulate the authors on a very well-researched and well-written publication." (Technometrics, August 2004, Vol. 46, No. 3) "...fascinating ...I highly recommend this book..." (Short Book Reviews, August 2004)"...a very well-researched and well-written publication." (Technometrics, August 2004)
More details
Product info
GB
Edition
1., Auflage
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 21 mm
Weight
630 gr
ISBN-13
978-0-470-84906-4 (9780470849064)
Schweitzer Classification
Other editions
New editions
Pierre Baldi | Paolo Frasconi | Padhraic Smyth
Modeling the Internet and the Web
Probabilistic Methods and Algorithms
Book
approx. 2030
2nd Edition
Wiley
€65.90
The article will not be published
Persons
Pierre Baldi is a chancellor's professor of computer science at University of California Irvine and the director of its Institute for Genomics and Bioinformatics. Paolo Frasconi is the author of Modeling the Internet and the Web: Probabilistic Methods and Algorithms, published by Wiley.
Content
Preface.
1 Mathematical Background.
1.1 Probability and Learning from a Bayesian Perspective.
1.2 Parameter Estimation from Data.
1.3 Mixture Models and the Expectation Maximization Algorithm.
1.4 Graphical Models.
1.5 Classification.
1.6 Clustering.
1.7 Power-Law Distributions.
1.8 Exercises.
2 Basic WWW Technologies.
2.1 Web Documents.
2.2 Resource Identifiers: URI, URL, and URN.
2.3 Protocols.
2.4 Log Files.
2.5 Search Engines.
2.6 Exercises.
3 Web Graphs.
3.1 Internet and Web Graphs.
3.2 Generative Models for theWeb Graph and Other Networks.
3.3 Applications.
3.4 Notes and Additional Technical References.
3.5 Exercises.
4 Text Analysis.
4.1 Indexing.
4.2 Lexical Processing.
4.3 Content-Based Ranking.
4.4 Probabilistic Retrieval.
4.5 Latent Semantic Analysis.
4.6 Text Categorization.
4.7 Exploiting Hyperlinks. 4.8 Document Clustering.
4.9 Information Extraction.
4.10 Exercises.
5 Link Analysis.
5.1 Early Approaches to Link Analysis.
5.2 Nonnegative Matrices and Dominant Eigenvectors.
5.3 Hubs and Authorities: HITS.
5.4 PageRank.
5.5 Stability.
5.6 Probabilistic Link Analysis.
5.7 Limitations of Link Analysis.
6 Advanced Crawling Techniques.
6.1 Selective Crawling.
6.2 Focused Crawling.
6.3 Distributed Crawling.
6.4 Web Dynamics.
7 Modeling and Understanding Human Behavior on the Web.
7.1 Introduction.
7.2 Web Data and Measurement Issues.
7.3 Empirical Client-Side Studies of Browsing Behavior.
7.4 Probabilistic Models of Browsing Behavior.
7.5 Modeling and Understanding Search Engine Querying.
7.6 Exercises.
8 Commerce on the Web: Models and Applications.
8.1 Introduction.
8.2 Customer Data on theWeb.
8.3 Automated Recommender Systems.
8.4 Networks and Recommendations.
8.5 Web Path Analysis for Purchase Prediction.
8.6 Exercises.
Appendix A Mathematical Complements.
A.1 Graph Theory.
A.2 Distributions.
A.3 Singular Value Decomposition.
A.4 Markov Chains.
A.5 Information Theory.
Appendix B List of Main Symbols and Abbreviations.
References.
Index.