Computers & Internet Books:

Graph Mining

Laws, Tools, and Case Studies

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Graph Mining by Deepayan Chakrabarti
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Description

What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with ""what if"" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous ""pageRank"" algorithm and the ""HITS"" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints.
Release date Australia
April 1st, 2010
Pages
207
Country of Publication
United States
Imprint
Morgan & Claypool Publishers
Dimensions
187x235x11
ISBN-13
9781608451159
Product ID
3723619

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