Fab: content-based, collaborative recommendation
Communications of the ACM
Experiences with selecting search engines using metasearch
ACM Transactions on Information Systems (TOIS)
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
SearchPad: explicit capture of search context to support Web search
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Web-collaborative filtering: recommending music by crawling the Web
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Towards a highly-scalable and effective metasearch engine
Proceedings of the 10th international conference on World Wide Web
Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
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With the explosion of the Internet, search engines are more and more popular. Up to now, most of the search engines will provide the same results to the different users on the same query. However, users may have their own sense of the same query and need personalized results. Also users are often not satisfied with the results primitively returned and need some mechanism for refining the results. In this work, we propose an on-line text distinguishers collection method under an interactive meta search framework. We also use those distinguishers to re-rank the search results to achieve the specific ranking order. Text distinguishers are defined as those words which can separate one document from others. They can be used to reflect the user's preference for a specific query.