Cooperative Query Processing via Knowledge Abstraction and Query Relaxation

Cooperative Query Processing via Knowledge Abstraction and Query Relaxation

Soon-Young Huh, Kae-Hyun Moon, Jin-Kyun Ahn
Copyright: © 2002 |Pages: 18
DOI: 10.4018/978-1-930708-41-9.ch011
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As database users adopt a query language to obtain information from a database, a more intelligent query answering system is increasingly needed that cooperates with the users to provide informative responses by understanding the intent behind a query. The effectiveness of decision support would improve significantly if the query answering system returned approximate answers rather than a null information response when there is no matching data available. Even when exact answers are found, neighboring information is still useful to users if the query is intended to explore some hypothetical information or abstract general fact. This chapter proposes an abstraction hierarchy as a framework to practically derive such approximate answers from ordinary everyday databases. 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 knowledge 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.

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