Automatically constructing multi-relationship fuzzy concept networks in fuzzy information retrieval systems

In this paper, an intelligent fuzzy information retrieval system with an automatically constructed knowledge base is presented. The knowledge base is represented by a multi-relationship fuzzy concept network that can depict the relationships and their associating relevance degrees between concepts clearly. Based on the multi-relationship fuzzy concept network architecture, the users of the fuzzy information retrieval system can submit a fuzzy contextual query that specifies the search context in the query formula. The fuzzy information retrieval system retrieves documents whose contents are relevant to the user´s query by some required relationships beneath a specified search context. The proposed fuzzy information retrieval method is more intelligent and more flexible than the existing methods since it can automatically construct knowledge bases (i.e, multi-relationship fuzzy concept networks) and it provides contextual search capability that allows users to specify fuzzy contextual queries in a more flexible manner.