Web mining applications in e-commerce and e-services
著者
書誌事項
Web mining applications in e-commerce and e-services
（Studies in computational intelligence, v. 172）
Springer, c2009
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Web mining has become a popular area of research, integrating the different research areas of data mining and the World Wide Web. According to the taxonomy of Web mining, there are three sub-fields of Web-mining research: Web usage mining, Web content mining and Web structure mining. These three research fields cover most content and activities on the Web. With the rapid growth of the World Wide Web, Web mining has become a hot topic and is now part of the mainstream of Web - search, such as Web information systems and Web intelligence. Among all of the possible applications in Web research, e-commerce and e-services have been iden- fied as important domains for Web-mining techniques. Web-mining techniques also play an important role in e-commerce and e-services, proving to be useful tools for understanding how e-commerce and e-service Web sites and services are used, e- bling the provision of better services for customers and users. Thus, this book will focus upon Web-mining applications in e-commerce and e-services. Some chapters in this book are extended from the papers that presented in WMEE 2008 (the 2nd International Workshop for E-commerce and E-services). In addition, we also sent invitations to researchers that are famous in this research area to contr- ute for this book. The chapters of this book are introduced as follows: In chapter 1, Peter I.
目次
Online Mining of Web Usage Data: An Overview.- Semantically Enhanced Web Personalization.- Semantics-Based Analysis and Navigation of Heterogeneous Text Corpora: The Porpoise News and Blogs Engine.- Semantic Analysis of Web Site Audience by Integrating Web Usage Mining and Web Content Mining.- Towards Web Performance Mining.- Anticipate Site Browsing to Anticipate the Need.- User Behaviour Analysis Based on Time Spent on Web Pages.- Ranking Companies on the Web Using Social Network Mining.- Adaptive E-Services Selection in P2P-Based Workflow with Multiple Property Specifications.- Web Mining Techniques for On-Line Social Networks Analysis: An Overview.
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