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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

by Bing Liu

Springer

Hardback or Cased Book 624 pages Jun 26, 2011

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Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
Author:
Bing Liu
Publisher:
Springer
Publication Date:
Jun 26, 2011
Number of pages:
624 pages
Binding:
Hardback or Cased Book
ISBN-10:
3642194591
ISBN-13:
9783642194597