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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications) ReviewSo what does the author, Bing Liu know about Web data mining to write the book "Web Data Mining - Exploring Hyperlinks, Contents, and Usage Data"[1] ? Fortunately the answer is "a lot!" This fact along with the title which had some cosine similarity with the names of my research lab and a graduate course that I have been teaching at the University of Louisville since 2004, and prior to that at the University of Memphis since 2000, are the reasons why I ordered a copy of this book. Bing Liu is a well seasoned researcher who has made significant contributions to association rule mining, in particular classification using association rule mining and association rule mining with multiple supports. He has also worked on Web data extraction, and more recently on opinion mining. In addition to the expertise of the author, two of the chapters, Chapter 8, Web Crawling, and Chapter 12, Web Usage Mining, were contributed by two leading experts in these respective areas, Filippo Menczer for the former and Bamshad Mobasher for the latter.This book is appropriate for students at the graduate or senior undergraduate level, for practitioners in industry, and even as a good comprehensive reference for researchers in academia.
The Table of Contents held a surprise for someone who had always found it hard to limit the number of textbooks to one book in a web mining course that does not have data mining as prerequisite, and thus typically prescribes a good data mining book to introduce data mining techniques, in addition to a second book related to web mining. This book, on the other hand, has two parts, one devoted to data mining, and the other devoted to Web mining. While it was not a problem to find a very good data mining book (I have a few of them on my bookshelf), it was harder to find a book that addressed data mining and Web mining. It was also hard to find a good and comprehensive Web mining book, since most of them tend to focus on one or only two of the three main Web mining areas of Web structure, content, and usage mining (typically leaving Web usage mining in the dark, with just a small section, citing that it is an emerging area). This book, on the other hand, is a serious book on Web mining that also devotes a decent portion to data mining. I would describe the way the topics are presented as deep and rigorous enough in most chapters, which is in contrast to a large number of books on data mining and web mining. That said, because the book is full of simple examples that illustrate the methods being discussed, it is useful even for beginners, making it also appropriate for an introductory level course.
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