Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
Data mining and the Web: past, present and future
Proceedings of the 2nd international workshop on Web information and data management
ACM SIGKDD Explorations Newsletter
Web user clustering from access log using belief function
Proceedings of the 1st international conference on Knowledge capture
Creating a Web community chart for navigating related communities
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
Ranking user's relevance to a topic through link analysis on web logs
Proceedings of the 4th international workshop on Web information and data management
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
The use of web structure and content to identify subjectively interesting web usage patterns
ACM Transactions on Internet Technology (TOIT)
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Web user search customization research has been fueled by the recognition that if the WWW is to attain to its optimal potential as an interactive medium the development of new and/or improved Web resource classification (page identification, referencing, indexing, etc) and retrieval/delivery systems supportive of and responsive to user preference is of prime importance. User preference, as it relates to a Web user's search agenda, entails maintaining the user as director of his search and expert as to which Web pages are relevant. In our work Web usage and Web structure mining are employed in a theoretically skillful way to produce a strongly connected virtual bipartite clique (biclique) search neighborhood of high quality pages of relevance to the Web user's search objective. Our algorithm is designed to exploit linkage data inherent in Web access logs using the Combined Log Format (CBLF) to assemble a referer partite set of pages consistent with the user's preference and search intent (members: user's initial choice of a Web resource/page and other relevant authority-type pages) and a request partite set (members: pages with incoming links from the referer partite). The Web user's initial page of choice becomes the first member of the referer partite and gatekeeper to the biclique neighborhood. Our algorithm uses a Web site's collective user's history (log entries) in a collaborative manner to identify and further qualify pages of relevance for membership in the appropriate partite set. Web user search customization strategically fostered by our algorithm enhances the efficiency and productivity of a Web user's activity in three ways: (1) it delivers high quality pages organized hierarchically to facilitate the user's ready assessment of the Web site's benefit to his search objective, thus minimizing time spent at an unfruitful site, (2) it facilitates ease of navigation in either breadth-first, depth-first or a combination of the two, and (3) it nullifies time spent locating and traversing paths to pages hosted in much-to-large distributed search environments.