Web Mining and Social Networking: Techniques and ... - tud.ttu.ee

1.5 Audience of This Book 11and user profiles via Web clustering and latent semantic analysis. At the end of thischapter, a number of Web usage mining applications are reported to show the applicationpotential in Web search and organization.Chapter 7 describes the research issues of Web social networking using Webmining. Web community mining is first addressed to indicate the capability of Webmining in social network analysis. Then it focuses on the topics of temporal characteristicsand dynamic evolutions of networked structures in the context of Websocial environments. To illustrate the application potential, a real world case study ispresented in this chapter along with some informative and valuable findings.Chapter 8 reviews the extension of Web mining in Web personalization and recommendation.Starting from the introduction the well-known collaborative filteringbased recommender systems, this chapter talks about the combination of Web usagemining and collaborative filtering for Web page and Web query recommendation.By presenting some empirical results from developed techniques and systems, thischapter gives the evidenced values of the integration of Web mining techniques withrecommendation systems in real applications.Chapter 9 concludes the research work included in this book, and outlines severalactive and hot research topics and open questions recently emerging in these areas.1.5 Audience of This BookThis book is aiming at a reference book for both academic researchers and industrialpractitioners who are working on the topics of Web search, information retrieval,Web data mining, Web knowledge discovery and social network analysis, the developmentof Web applications and the analysis of social networking. This book can alsobe used as a text book for postgraduate students and senior undergraduate studentsin Computer Science, Information Science, Statistics and Social Behavior Science.This book has the following features:• systematically presents and discusses the mathematical background and representativealgorithms for Web mining, Web community analysis and social networkingas well;• thoroughly reviews the related studies and outcomes conducted on the addressedtopics;• substantially demonstrates various important applications in the areas of Webmining, Web community and social behavior and network analysis; and• heuristically outlines the open research questions of the inter-disciplinary researchtopics, and identifies several future research directions that readers maybe interested in.