A data abstraction approach for query relaxation

Since a query language is used as a handy tool to obtain information from a database, users want more user-friendly and fault-tolerant query interface s. When a query search condition does not match with the underlying databas e, users would rather receive approximate answers than null information by relaxing the condition. They also prefer a less rigid querying structure, o ne which allows for vagueness in composing queries, and want the system to understand the intent behind a query. This paper presents a data abstractio n approach to facilitate the development of such a fault-tolerant and intel ligent query processing system. It specifically proposes a knowledge abstra ction database that adopts a multilevel knowledge representation scheme cal led the knowledge abstraction hierarchy. Furthermore, the knowledge abstrac tion database extracts semantic data relationships from the underlying data base and supports query relaxation using query generalization and specializ ation steps. Thus, ii: can broaden the search scope of original queries to retrieve neighborhood information and help users to pose conceptually abstr act queries. Specifically, four types of vague queries are discussed, inclu ding approximate selection, approximate join, conceptual selection and conc eptual join. (C) 2000 Elsevier Science B.V. All rights reserved.