Providing approximate answers using a knowledge abstraction database

Abstract

As database users adopt a query language to obtain information from a database, a more intelligent query answering system is increasingly needed. Relational databases are exact in nature, but effectiveness of decision support would improve significantly if the query answering system returns approximate answers rather than a null information response when there is no matching data available. This paper proposes an abstraction hierarchy as a framework to practically derive such approximate answers from ordinary everyday database. It provides a knowledge abstraction database to facilitate the approximate query answering. The knowledge abstraction database specifically adopts an abstraction approach to extract semantic data relationships from the underlying database, and uses a multi-level hierarchy for coupling multiple levels of abstraction knowldege and data values. In cooperation with the underlying database, the knowledge abstraction database allows the relaxation of query conditions so that the original query scope can be broadened and thus information approximate to exact answers can be obtained. Conceptually abstract queries can also be posed to provide a less rigid query interface. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database systems.