Knowledge Discovery for Flexible Querying

We present an approach to exible querying by exploiting similarity knowledge hidden in the information base. The knowledge represents associations between the terms used in descriptions of objects. Central to our approach is a method for mining the database for similarity knowledge, representing this knowledge in a fuzzy relation, and utilizing it in softening of the query. The approach has been implemented, and an experiment has been carried out on a real-world bibliographic database. The experiments demonstrated that without much sophistication in the system, we can automatically to derive domain knowledge that corresponds to human intuition, and utilize this knowledge to obtain a considerable increase in the quality of the search system.