A fuzzy information retrieval method using fuzzy-valued concept networks

We present a fuzzy information retrieval method based on fuzzy-valued concept networks, where the relevant degree between any two concepts in a fuzzy-valued concept network is represented by arbitrary shapes of fuzzy numbers. There are two kinds of relevant relationships between any two concepts in a fuzzy-valued concept network (i.e., fuzzy positive association and fuzzy negative association). In order to reduce the time of fuzzy inference, the relevant matrices and the relationship matrices are used to model the fuzzy-valued concept networks. The elements of a relevant matrix represent the relevant degrees between concepts. The elements of a relationship matrix represent the relevant relationships between concepts. Furthermore, we also allow users´ queries to be represented by arbitrary shapes of fuzzy numbers and to use the fuzzy positive association relationship and the fuzzy negative association relationship for formulating their queries in order to increase the flexibility of fuzzy information retrieval systems. We also present a fuzzy information retrieval method based on the network-type fuzzy-valued concept network architecture in the Internet environment