TileBars: visualization of term distribution information in full text information access
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating document clustering for interactive information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Further Experiments on Collaborative Ranking in Community-Based Web Search
Artificial Intelligence Review
Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
User Modeling and User-Adapted Interaction
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Collecting community wisdom: integrating social search & social navigation
Proceedings of the 12th international conference on Intelligent user interfaces
ASSIST: adaptive social support for information space traversal
Proceedings of the eighteenth conference on Hypertext and hypermedia
(Web Search)shared: Social Aspects of a Collaborative, Community-Based Search Network
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Information recovery and discovery in collaborative web search
ECIR'07 Proceedings of the 29th European conference on IR research
Artifact-mediated society and social intelligence design
Artificial intelligence
Social summarization in collaborative web search
Information Processing and Management: an International Journal
Extraction, characterization and utility of prototypical communication groups in the blogosphere
ACM Transactions on Information Systems (TOIS)
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Collaborative Web search (CWS) is an approach to personalizing search results, returned by an underlying search engine(s), to the preferences of a community of like-minded searchers. In this paper we propose an alternative architecture that facilitates a more flexible integration between CWS and the underlying search engine(s) and evaluate how community behaviour can be used to annotate search results with explanatory information to facilitate relevancy judgments.