Web Data Mining
Exploring Hyperlinks, Contents, and Usage Data
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Beschreibung
The rapid growth of the Web in the last decade makes it the largest p- licly accessible data source in the world. Web mining aims to discover u- ful information or knowledge from Web hyperlinks, page contents, and - age logs. Based on the primary kinds of data used in the mining process, Web mining tasks can be categorized into three main types: Web structure mining, Web content mining and Web usage mining. Web structure m- ing discovers knowledge from hyperlinks, which represent the structure of the Web. Web content mining extracts useful information/knowledge from Web page contents. Web usage mining mines user access patterns from usage logs, which record clicks made by every user. The goal of this book is to present these tasks, and their core mining - gorithms. The book is intended to be a text with a comprehensive cov- age, and yet, for each topic, sufficient details are given so that readers can gain a reasonably complete knowledge of its algorithms or techniques without referring to any external materials. Four of the chapters, structured data extraction, information integration, opinion mining, and Web usage mining, make this book unique. These topics are not covered by existing books, but yet they are essential to Web data mining. Traditional Web mining topics such as search, crawling and resource discovery, and link analysis are also covered in detail in this book.
Covers all key tasks and techniques of Web search and Web mining, i.e., structure mining, content mining, and usage mining First book with such a comprehensive coverage Includes major algorithms from data mining, machine learning, information retrieval and text processing, which are crucial for many Web mining tasks First self-contained book Contains a rich blend of theory and practice, addressing seminal research ideas and also looking at the technology from a practical point of view Ideally suited for classes on Data Mining, Web Mining, Web Search, and Knowledge Discovery in Data Bases Provides internet support with lecture slides and project problems Includes supplementary material: sn.pub/extras
This is the first book to provide such a comprehensive text on Web data mining. The 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.
It contains 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. Internet support with lecture slides and project problems is available online.
Autor*in
Bing Liu
Themen in »Web Data Mining«
Perl Web Crawling Web Data Mining algorithms data mining learning machine learning web mining
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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)
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