Intelligent fuzzy information retrieval based on ontology knowledge-base

Abstract

Intelligent fuzzy information retrieval (IR) based on ontology knowledge base has become one of the most active research directions in the field of intelligent IR system. How to use ontology knowledge base to further improve its retrieval performance and intelligence has become the main research goal of intelligent fuzzy IR system based on ontology knowledge-base. IR using knowledge organisation can improve the quality between returning document and user's initial query. The intelligent fuzzy information retrieval model proposed in this paper can provide a coded knowledge-base structure for IR, which is composed of multiple related ontologies, and the relationship between ontology is expressed as fuzzy relationship. In this kind of knowledge organisation, a new method is used to extend user's initial query and index document set, which independently represents ontology and the relationship between concepts. The experimental results show that the proposed model has a better overall performance compared with the other classical IR method. The prospects for future development and suggestions for possible extensions of the ontology knowledge base-based intelligent fuzzy IR systems are also discussed.