Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Communications of the ACM
Building and applying a concept hierarchy representation of a user profile
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
A community-aware search engine
Proceedings of the 13th international conference on World Wide Web
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Clustering For Data Mining: A Data Recovery Approach (Chapman & Hall/Crc Computer Science)
Clustering For Data Mining: A Data Recovery Approach (Chapman & Hall/Crc Computer Science)
Context-sensitive information retrieval using implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
The Wisdom of Crowds
Learning user interaction models for predicting web search result preferences
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Web dynamics and their ramifications for the development of web search engines
Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics
Dynamically constructing user profiles with similarity-based online incremental clustering
International Journal of Advanced Intelligence Paradigms
Robustness of dynamic social networks
Journal of Mobile Multimedia
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In the situation of information overload we are experiencing today, conventional web search systems taking a one-size-fits-all approach are often not capable of effectively satisfy individual information needs. To improve the quality of web information retrieval, we propose a collaborative personalised search approach that makes an attempt to 'understand' and better satisfy the information needs for each and every searching user. We present a web information retrieval framework called Better Search and Sharing (BESS) that captures user-system interactions, profiles them and induces personal interests that changes over time with an interest-change-driven profiling mechanism that is also extensively used for the co-evaluation of documents found valuable inside a specific search context by users with similar interests.