Automatically constructing multi-relationship fuzzy concept networks for document retrieval

Although the knowledge bases incorporated in existing information retrieval systems can enhance retrieval effectiveness, many of them are built by domain experts. It is obvious that the construction of such knowledge bases requires a large amount of human effort. 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. The multi-relationship fuzzy concept network can describe four kinds of context-independent and context-dependent fuzzy relationships, i.e., "fuzzy positive association" relationship, "fuzzy negative association" relationship, "fuzzy generalization" relationship, and "fuzzy specialization" relationship between concepts. The users of the fuzzy information retrieval system can submit a fuzzy contextual query which 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 kinds of fuzzy relationships for the specified search context of the user's query. The proposed fuzzy information retrieval method is more intelligent and more flexible than the existing methods due to the fact that it can construct multi-relationship fuzzy concept networks automatically and it can provide contextual search capability to allow the users to specify fuzzy contextual queries in a more intelligent and flexible manner.