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Users' models of the information space: the case for two search models
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
A case-based approach to intelligent information retrieval
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
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CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
Collaborative relevance judgment: a group consensus method for evaluating user search performance
Journal of the American Society for Information Science and Technology
User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
Web Intelligence and Agent Systems
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Data & Knowledge Engineering - Special issue: ER 2004
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Journal of Information Science
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Applied Artificial Intelligence
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EC-Web'05 Proceedings of the 6th international conference on E-Commerce and Web Technologies
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Over the past few years, the amount of electronic informationavailable through the Internet has increased dramatically.Unfortunately, the search tools currently available for retrieving andfiltering information in this space are not effective in balancingrelevance and comprehensiveness. This paper analyzes the results ofexperiments in which HTML documents are searched with user models andsoftware agents used as intermediaries to the search. Simple usermodels are first combined with search specifications (or ’UserNeeds‘), to define an Enhanced User Need. Then UniformResource Agents are constructed to filter information based on the EUNparameters. The results of searches using different agents are thencompared to those obtained through a comparable simple keyword search,and it is shown that a user searching a pool of existing agents canobtain better search results than by conducting a traditional keywordsearch. This work thus demonstrates that the use of user models andinformation filtering agents do improve search results and may be usedto improve Internet information retrieval.