Context-sensitive text mining and belief revision for intelligent information retrieval on the web
Web Intelligence and Agent Systems
Optimization of some factors affecting the performance of query expansion
Information Processing and Management: an International Journal
Integration of association rules and ontologies for semantic query expansion
Data & Knowledge Engineering
Integration of association rules and ontologies for semantic query expansion
Data & Knowledge Engineering
International Journal of Business Intelligence and Data Mining
A semantic-expansion approach to personalized knowledge recommendation
Decision Support Systems
A probabilistic topic model with social tags for query reformulation in informational search
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Learning a Lightweight Ontology for Semantic Retrieval in Patient-Centered Information Systems
International Journal of Knowledge Management
Using semantic-based association rule mining for improving clinical text retrieval
HIS'13 Proceedings of the second international conference on Health Information Science
Correlating medical-dependent query features with image retrieval models using association rules
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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In this paper, we are looking at the mining of association between terms for the automatic expansion of queries. The technique we use for the discovery of the associations is association rules mining [9]. The technique we propose is more flexible than previous techniques based on term co-occurrence since it takes into account not only the co-occurrence frequency but also the confidence and direction of the association rules. We have been able to consistently improve the effectiveness of the retrieval over the set of 48 test queries on the Associated Press 1990 news wires corpus of the TREC4 benchmark by query expansion using term association rules.