Description:
Now in its second, updated edition, this authoritative and coherent text contains a rich blend of theory and practice and covers all the essential concepts and algorithms from relevant fields such as data mining, machine learning, and text processing.
Review Quotes:
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." ACM Computing Reviews, W. Hu, January 2009
From the reviews of the second edition:
"Liu (Univ. of Illinois, Chicago) discusses all three types of Web mining--structure, content, and usage--in the technology's efforts to glean information from hyperlinks, Web page content, and usage logs. [...] Practical examples complement the discussions throughout the text, and each chapter includes useful 'Bibliographic Notes' and an extensive bibliography. [...] Liu states that his intended audience includes bothundergraduate and graduate students, but notes that researchers and Web programmers could benefit from this text as well. Summing Up: Recommended. Upper-division undergraduates through professionals." J. Johnson, Choice, Vol. 49 (5), January 2012
"[...] Liu's book provides a comprehensive, self-contained introduction to the major data mining techniques and their use in Web data mining. [...] Professionals and researchers alike will find this excellent book handy as a reference. Its extensive lists of references at the end of each chapter provide hundreds of pointers for further reading. As a textbook, it is also suitable for advanced undergraduate and graduate courses on Web mining; it is highly selfcontained and includes many easy-to-understand examples that will help readers grasp the key ideas behind current Web data mining techniques." ACM Computing Reviews, Fernando Berzal, February 2012