Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Automatic resource compilation by analyzing hyperlink structure and associated text
WWW7 Proceedings of the seventh international conference on World Wide Web 7
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Mining navigation history for recommendation
Proceedings of the 5th international conference on Intelligent user interfaces
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Document clustering with committees
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
Integrating Web Usage and Content Mining for More Effective Personalization
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Enabling Personalized Recommendation on the Web Based on User Interests and Behaviors
RIDE '01 Proceedings of the 11th International Workshop on research Issues in Data Engineering
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Web recommender systems anticipate the information needs of on-line users and provide them with recommendations to facilitate and personalize their navigation. There are many approaches to building such systems. Among them, using web access logs to generate users’ navigational models capable of building a web recommender system is a popular approach, given its non-intrusiveness. However, using only one information channel, namely the web access history, is often insufficient for accurate recommendation prediction. We therefore advocate the use of additional available information channels, such as the content of visited pages and the connectivity between web resources, to better model user navigational behavior. This helps in better modeling users’ concurrent information needs. In this chapter, we investigate a novel hybrid web recommender system, which combines access history and the content of visited pages, as well as the connectivity between web resources in a web site, to model users’ concurrent information needs and generate navigational patterns. Our experiments show that the combination of the three channels used in our system significantly improves the quality of web site recommendation and, further, that each additional channel used contributes to this improvement. In addition, we discuss cases on how to reach a compromise when not all channels are available.