Search Engines, Link Analysis, and User's Web Behavior
George Meghabghab
- 28 oktober 2010
- 9783642096167
Samenvatting:
This book presents a specific and unified approach framework to three major components: Search Engines Performance, Link Analysis, and User’s Web Behavior. The explosive growth and the widespread accessibility of the WWW has led to a surge of research activity in the area of information retrieval on the WWW. The book can be used by researchers in the fields of information sciences, engineering (especially software), computer science, statistics and management, who are looking for a unified theoretical approach to finding relevant information on the WWW and a way of interpreting it from a data perspective to a user perspective. It specifically stresses the importance of the involvement of the user looking for information to the relevance of information sought to the performance of the medium used to find information on the WWW.
WEB MINING Link Analysis Search Engines User’s Web Behavior HITS Algorithm Fuzzy Cognitive Map Radial Basis Function PageRank Algorithm Interior Point Method Fuzzy Bags Rgeression Models Rough Sets Information Theory Thisbookpresentsaspeci?cand uni?ed approach framework to three- jor components: Search Engines Performance, Link Analysis, and User’s Web Behavior. TheexplosivegrowthandthewidespreadaccessibilityoftheWWW has led to a surge of research activity in the area of information retrieval on VI Preface the WWW. The three aspects of web mining follow the taxonomy of the above diagram: Link Analysis, Search engines, and User’s web behavior are considered in the unifying approach. The book is organized in three sections as follows: 1. In section I of the book (chapters 2–4) we study Link Analysis within the hubs and authorities framework. Link Analysis is the science of hyperlink structures ranking, which are used to determine the relative authority of a Web page and produce improved algorithms for the ranking of Web search results. We use the HITS Algorithm developed by Kleinberg and we propose to study HITS in a 2-D new space: In-degree and Out Degree variables. After we categorize each web page into a speci?c toplogy we study the impact of each web topology on HITS in the new 2-D space. We describe why HITS does not fare well in almost all the di?erent topologies of web graphs. We also describe the PageRank Algorithm in this new 2-D space.