Fuzzy query processing for document retrieval based on extended fuzzy concept networks

Abstract

In this paper, we present a new method for fuzzy query processing for document retrieval based on extended fuzzy concept networks. In an extended fuzzy concept network, there are four kinds of fuzzy relationships between concepts, i.e., fuzzy positive association, fuzzy negative association, fuzzy generalization, and fuzzy specialization, An extended fuzzy concept network can be modeled by a relation matrix and a relevance matrix, where the elements in a relation matrix represent the fuzzy relationships between concepts, and the elements in a relevance matrix indicate the degrees of relevance between concepts. The implicit fuzzy relationships between concepts can be inferred by the transitive closure of the relation matrix. The implicit degrees of relevance between concepts also can be inferred by the transitive closure of the relevance matrix. The proposed method is more flexible than the ones presented in [8] and [17] due to the fact that it allows the users to perform positive queries, negative queries, generalization queries, and specialization queries. The proposed method allows the users to perform fuzzy queries in a more flexible and more intelligent manner.