On modeling of information retrieval concepts in vector spaces
ACM Transactions on Database Systems (TODS)
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Fab: content-based, collaborative recommendation
Communications of the ACM
A vector space model for automatic indexing
Communications of the ACM
Communications of the ACM - Supporting community and building social capital
Modern Information Retrieval
The many faces of publish/subscribe
ACM Computing Surveys (CSUR)
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Bringing knowledge into recommender systems
Journal of Systems and Software
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Navigating the web with its large number of resources can sometimes be hard. Web-based communities form as individuals get together to discuss and exchange information. These communities provide a nexus around which individuals organise and learn. As they grow and accumulate shared resources, they become rich information sources. The usual way to navigate the web is to search, starting from a search page and then browsing to look for adequate resources. However, when looking for information, individuals often turn to others for recommendations or answers. This paper presents a peer-to-peer tool to assist in web navigation and searches by leveraging a community's existing knowledge. Individuals rate websites and share these ratings with the community. Recommendations are made based on these ratings. This enables a community-geared rating, where individuals know they will find ratings that reflect the opinions of the community in which he or she is inserted. This mimics recommendation-seeking behaviour and has the potential to lead to better results as searches become more directed towards a community's context.