Concept based retrieval in classical IR systems
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Information Retrieval
Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A. Zadeh
Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A. Zadeh
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Semantic cores for representing documents in IR
Proceedings of the 2005 ACM symposium on Applied computing
Concept-Based Term Weighting for Web Information Retrieval
ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
Evolutionary Computation
Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Hi-index | 0.00 |
We propose an approach to user model-based information retrieval which uses an evolutionary algorithm to learn fuzzy models of user interests and to dynamically track their changes as the user interacts with the system. The system is ontology-based, in the sense that it considers concepts behind terms instead of simple terms. The approach has been implemented in a real-world prototype newsfeed aggregator with search facilities called IFeed. Experimental results show that our system learns user models effectively. This is proved by both the convergence of the interest degrees contained in the user models population and the increase of the users' activities on the set of proposed documents.