A KNOWLEDGE-BASED SYSTEM FOR CORRECTING USERS MISCONCEPTIONS IN DATABASE RETRIEVAL

A Cooperative Response system, which can detect and correct users' misconceptions exhibited in database retrieval, is one of the most promising ways for applying the knowledge engineering approach to traditional database query systems. Misconceptions are generally regarded as users' false beliefs about a database and are considered as a main source of failures in the database retrieval. How to handle users' false beliefs has recently become an important point to overcome in advanced database front-end development. While many efforts have been made to develop cooperative response systems, most of the work has placed emphasis on the detection of a user's false beliefs revealed in a single query. No attention has been paid to handle users' inconsistent beliefs which would be revealed in a sequence of contextual queries. In this paper, we propose a user-beliefs-modeling approach for detecting the inconsistent beliefs exhibited in two contextual queries. As an extension of the existing cooperative response systems, the system proposed in this paper can generate informative responses to correct users' inconsistent beliefs.