{"product_id":"modeling-the-internet-and-the-web-probabilistic-methods-and-algorithms-hardback-9780470849064","title":"Modeling the Internet and the Web; Probabilistic Methods and Algorithms (Hardback) 9780470849064","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eModeling the Internet and the Web\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eProbabilistic Methods and Algorithms\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003ePierre Baldi (Author), Paolo Frasconi (Author), Padhraic Smyth (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470849064, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 25 April 2003\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e306 pages\u003cbr\u003e23.2 x 15.9 x 2.3 cm, 0.595 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\"…I congratulate the authors on a very well-researched and well-written publication.\" (\u003ci\u003eTechnometrics\u003c\/i\u003e, August 2004, Vol. 46, No. 3)  \u003cp\u003e“…fascinating …I highly recommend this book…” (Short Book Reviews, August 2004)\u003c\/p\u003e \u003cp\u003e“…a very well-researched and well-written publication.” (Technometrics, August 2004) \u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eModeling 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.  \u003cp\u003e Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.\u003cbr\u003e  Takes a modern approach based on mathematical, probabilistic, and graphical modeling.\u003cbr\u003e  Provides an integrated presentation of theory, examples, exercises and applications.\u003cbr\u003e  Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web.\u003c\/p\u003e \u003cp\u003eInterdisciplinary 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.\u003c\/p\u003e \u003cp\u003e\"This book is fascinating!\" - David Hand (Imperial College, UK)\u003c\/p\u003e \u003cp\u003e\"This book provides an extremely useful introduction to the intellectually stimulating problems of data mining electronic business.\" - Andreas S. Weigend (Chief Scientist, Amazon.com)\u003cbr\u003e \u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003e\u003cb\u003e1 Mathematical Background.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Probability and Learning from a Bayesian Perspective.\u003c\/p\u003e \u003cp\u003e1.2 Parameter Estimation from Data.\u003c\/p\u003e \u003cp\u003e1.3 Mixture Models and the Expectation Maximization Algorithm.\u003c\/p\u003e \u003cp\u003e1.4 Graphical Models.\u003c\/p\u003e \u003cp\u003e1.5 Classification.\u003c\/p\u003e \u003cp\u003e1.6 Clustering.\u003c\/p\u003e \u003cp\u003e1.7 Power-Law Distributions.\u003c\/p\u003e \u003cp\u003e1.8 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Basic WWW Technologies.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Web Documents.\u003c\/p\u003e \u003cp\u003e2.2 Resource Identifiers: URI, URL, and URN.\u003c\/p\u003e \u003cp\u003e2.3 Protocols.\u003c\/p\u003e \u003cp\u003e2.4 Log Files.\u003c\/p\u003e \u003cp\u003e2.5 Search Engines.\u003c\/p\u003e \u003cp\u003e2.6 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Web Graphs.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Internet and Web Graphs.\u003c\/p\u003e \u003cp\u003e3.2 Generative Models for the Web Graph and Other Networks.\u003c\/p\u003e \u003cp\u003e3.3 Applications.\u003c\/p\u003e \u003cp\u003e3.4 Notes and Additional Technical References.\u003c\/p\u003e \u003cp\u003e3.5 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Text Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Indexing.\u003c\/p\u003e \u003cp\u003e4.2 Lexical Processing.\u003c\/p\u003e \u003cp\u003e4.3 Content-Based Ranking.\u003c\/p\u003e \u003cp\u003e4.4 Probabilistic Retrieval.\u003c\/p\u003e \u003cp\u003e4.5 Latent Semantic Analysis.\u003c\/p\u003e \u003cp\u003e4.6 Text Categorization.\u003c\/p\u003e \u003cp\u003e4.7 Exploiting Hyperlinks.\u003c\/p\u003e \u003cp\u003e4.8 Document Clustering.\u003c\/p\u003e \u003cp\u003e4.9 Information Extraction.\u003c\/p\u003e \u003cp\u003e4.10 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Link Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Early Approaches to Link Analysis.\u003c\/p\u003e \u003cp\u003e5.2 Nonnegative Matrices and Dominant Eigenvectors.\u003c\/p\u003e \u003cp\u003e5.3 Hubs and Authorities: HITS.\u003c\/p\u003e \u003cp\u003e5.4 PageRank.\u003c\/p\u003e \u003cp\u003e5.5 Stability.\u003c\/p\u003e \u003cp\u003e5.6 Probabilistic Link Analysis.\u003c\/p\u003e \u003cp\u003e5.7 Limitations of Link Analysis.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Advanced Crawling Techniques.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Selective Crawling.\u003c\/p\u003e \u003cp\u003e6.2 Focused Crawling.\u003c\/p\u003e \u003cp\u003e6.3 Distributed Crawling.\u003c\/p\u003e \u003cp\u003e6.4 Web Dynamics.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Modeling and Understanding Human Behavior on the\u003c\/b\u003e \u003cb\u003eWeb.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction.\u003c\/p\u003e \u003cp\u003e7.2 Web Data and Measurement Issues.\u003c\/p\u003e \u003cp\u003e7.3 Empirical Client-Side Studies of Browsing Behavior.\u003c\/p\u003e \u003cp\u003e7.4 Probabilistic Models of Browsing Behavior.\u003c\/p\u003e \u003cp\u003e7.5 Modeling and Understanding Search Engine Querying.\u003c\/p\u003e \u003cp\u003e7.6 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Commerce on the Web: Models and Applications.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 Customer Data on theWeb.\u003c\/p\u003e \u003cp\u003e8.3 Automated Recommender Systems.\u003c\/p\u003e \u003cp\u003e8.4 Networks and Recommendations.\u003c\/p\u003e \u003cp\u003e8.5 Web Path Analysis for Purchase Prediction.\u003c\/p\u003e \u003cp\u003e8.6 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Mathematical Complements.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Graph Theory.\u003c\/p\u003e \u003cp\u003eA.2 Distributions.\u003c\/p\u003e \u003cp\u003eA.3 Singular Value Decomposition.\u003c\/p\u003e \u003cp\u003eA.4 Markov Chains.\u003c\/p\u003e \u003cp\u003eA.5 Information Theory.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B: List of Main Symbols and Abbreviations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mathematics [\u003ca title=\"See our other books on Mathematics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mathematics%20%5BPB%5D%22\"\u003ePB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand 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