These topics are not covered by existing books, but yet they are essential to Web data mining. Four of the chapters, structured data extraction, information integration, opinion mining, and Web usage mining, make this book unique. 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. The goal of this book is to present these tasks, and their core mining - gorithms. Web usage mining mines user access patterns from usage logs, which record clicks made by every user. Web content mining extracts useful information/knowledge from Web page contents. Web structure m- ing discovers knowledge from hyperlinks, which represent the structure of the Web. 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 mining aims to discover u- ful information or knowledge from Web hyperlinks, page contents, and - age logs. The rapid growth of the Web in the last decade makes it the largest p- licly accessible data source in the world.
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