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Producing Monotonically Improving Approximate Answers to Database Queries

  • Susan V. Vrbsky
  • Jane W. S. Liu
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 318)

Abstract

For some applications, it may be better for a database to produce an approximate answer when it is not possible to produce an exact answer to a database query. An approximate query processor, called APPROXIMATE, makes approximate answers available if part of the database is unavailable or if there is not enough time to produce an exact answer. The processor implements monotone approximate query processing — the accuracy of the approximate result produced improves monotonically with the amount of data retrieved to produce the result. The query processing algorithm of APPROXIMATE works within a standard relational algebra framework. APPROXIMATE maintains semantic information for approximate query processing and can be implemented on a relational database system with little change to the relational architecture. We describe how the approximation semantics of APPROXIMATE serve as the basis for meaningful approximations of queries with set-valued or single-valued answers and how APPROXIMATE is implemented to make effective use of the semantic information.

Keywords

Data Object Query Processing Database Query Exact Answer Aggregate Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Susan V. Vrbsky
    • 1
  • Jane W. S. Liu
    • 2
  1. 1.Department of Computer ScienceUniversity of AlabamaTuscaloosaUSA
  2. 2.Department of Computer ScienceUniversity of IllinoisUrbanaUSA

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