Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
Mining web logs to improve website organization
Proceedings of the 10th international conference on World Wide Web
Web montage: a dynamic personalized start page
Proceedings of the 11th international conference on World Wide Web
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Web-Log Mining for Predictive Web Caching
IEEE Transactions on Knowledge and Data Engineering
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Adaptive web sites: cluster mining and conceptual clustering for index page synthesis
Adaptive web sites: cluster mining and conceptual clustering for index page synthesis
Smartback: supporting users in back navigation
Proceedings of the 13th international conference on World Wide Web
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
Proceedings of the 13th international conference on World Wide Web
Adaptive web sites: an AI challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Adaptive web navigation for wireless devices
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
WebKDD 2006: web mining and web usage analysis post-workshop report
ACM SIGKDD Explorations Newsletter
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Visitors enter a website through a variety of means, including web searches, links from other sites, and personal bookmarks. In some cases the first page loaded satisfies the visitor's needs and no additional navigation is necessary. In other cases, however, the visitor is better served by content located elsewhere on the site found by navigating links. If the path between a user's current location and his eventual goal is circuitous, then the user may never reach that goal or will have to exert considerable effort to reach it. By mining site access logs, we can draw conclusions of the form "users who load page p are likely to later load page q." If there is no direct link from p to q, then it is advantageous to provide one. The process of providing links to users' eventual goals while skipping over the in-between pages is called shortcutting. Existing algorithms for shortcutting require substantial offline training, which make them unable to adapt when access patterns change between training sessions. We present improved online algorithms for shortcut link selection that are based on a novel analogy drawn between shortcutting and caching. In the same way that cache algorithms predict which memory pages will be accessed in the future, our algorithms predict which web pages will be accessed in the future. Our algorithms are very efficient and are able to consider accesses over a long period of time, but give extra weight to recent accesses. Our experiments show significant improvement in the utility of shortcut links selected by our algorithm as compared to those selected by existing algorithms.