Table of Contents

1) Introduction - 2) Association Rules and Sequential Patterns - 3) Supervised Learning - 4) Unsupervised Learning - 5) Partially Supervised Learning - 6) Information Retrieval and Web Search - 7) Link Analysis - 8) Web Crawling - 9) Structured Data Extraction: Wrapper Generation - 10) Information Integration - 11) Opinion Mining - 12) Web Usage Mining - References, Index

About the Author

Bing Liu is an associate professor in Computer Science at the University of Illinois at Chicago (UIC). He received his PhD degree in Artificial Intelligence from the University of Edinburgh. Before joining UIC in 2002, he was with the National University of Singapore. His research interests include data mining, Web mining, text mining, and machine learning. He has published extensively in these areas in leading conferences and journals. He served (or serves) as a vice chair, deputy vice chair or program committee member of many conferences, including WWW, KDD, ICML, VLDB, ICDE, AAAI, SDM, CIKM and ICDM.

Reviews

From the reviews: "This is a textbook about data mining and its application to the Web. ! Liu succeeds in helping readers appreciate the key role that data mining and machine learning play in Web applications. ! It also motivates the student by adding immediacy and relevance to the concepts and algorithms described. I liked the way the concepts are introduced in a stepwise manner. ! I also appreciated the bibliographical notes at the end of each chapter." (W. Hu, ACM Computing Reviews, January, 2009)