Intelligent query answering based on neighborhood systems and data mining techniques

We investigate the application of neighborhood systems and data mining techniques for intelligence query answering in the database systems. This work proposes an intelligent query answering technique that integrates neighborhood information and data mining rules discovered from the databases. Neighborhood systems handle the notions of close to, analogous to and approximate t, and provide the user´s background information such as preference, interests, needs etc, while the knowledge rules discovered by the data mining methods have the summary, statistical or generalized information about the databases. The neighborhood information is incorporated into the query rewriting process to help the systems rewrite the original query, and data mining rules are used to help answer the queries more intelligently, effectively and efficiently.