This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).
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" it has to be noted that this book is an excellent resource for conducting Web mining lectures or single units within Data mining class. The data can be used for small as well as quite comprehensive business intelligence projects. The book′s content is easy to access; even students with very basic statistical skills can get the flavor of the intriguing aspects of Web mining." ( Journal of Statistical Software, April 2008)
" highlight[s] the exciting research related to data mining the Web a detailed summary of the current state of the art." (CHOICE, December 2007)
"I can say I really enjoyed reading this book a great educational resource for students and teachers." (Information Retrieval, 2008)
Zdravko Markov, PhD, is Associate Professor of Computer Science at Central Connecticut State University. The author of three textbooks, Dr. Markov teaches undergraduate and graduate courses in computer science and artificial intelligence. He is currently a Principal Investigator (PI) in a National Science Foundation–funded project designed to introduce machine learning to undergraduates.
Daniel T. Larose, PhD, is Professor of Statistics in the Department of Mathematical Sciences at Central Connecticut State University. He is the author of three data mining books and a forthcoming textbook in undergraduate statistics. He developed and directs CCSU's DataMining@CCSU programs.
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