Relevance feedback and other query modification techniques
Information retrieval
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Combining numerical and linguistic information in group decision making
Information Sciences: an International Journal
Fusion of multi-agent preference orderings
Fuzzy Sets and Systems
Performance measurement in a fuzzy retrieval environment
SIGIR '81 Proceedings of the 4th annual international ACM SIGIR conference on Information storage and retrieval: theoretical issues in information retrieval
Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Intelligent filtering with genetic algorithms and fuzzy logic
Technologies for constructing intelligent systems
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In this work, we present a method to characterize a given topic on an Information Retrieval System based on expert user profiles. We start from a set of documents from which a set of characteristic terms is extracted. The presence of any term in each document is known and we want to establish the most significant ones in order to select relevant documents about a given topic II. For that purpose, a group of experts are required to assess the set of documents. The experts can query with the same terms (an unique query) to the system or with different terms (several queries). By aggregating these assessments with the weight associated to the terms, a topic profile can be obtained. An overview of these different situations and an experimental example are also presented.