Fuzzy ontologies for search results diversification
Ghada Besbes, Hajer Baazaoui Zghal · 2018
Fuzzy ontologies offer an efficient representation of uncertain information in natural language and this representation allows a better interpretation of user queries and documents. Integrating fuzzy ontologies in a search results diversification process may improve the quality of returned documents since diversification helps covering the maximum of user's needs. In this context, we propose an ontology based diversification approach for search results applied to medical domain. The proposal first analyses the query in order to extract medical concepts. A contextual ontology fuzzification is then applied in order to offer an understanding of the user's information needs and finally a fuzzy search result diversification is performed in order to improve the ranking quality of returned documents. We perform a thorough experimental evaluation of our proposal with CLEF e-health 2016 topics. Evaluation results show a major improvement in precision and ranking.