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)
Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search.
Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.