Approximate query mapping: Accounting for translation closeness |
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Authors: | Kevin Chen-Chuan Chang Héctor García-Molina |
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Affiliation: | (1) Computer Science Department, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; e-mail: kcchang@cs.uiuc.edu , US;(2) Computer Science Department, Stanford University, Stanford, CA 94305, USA; E-mail: hector@db.stanford.edu , US |
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Abstract: | In this paper we present a mechanism for approximately translating Boolean query constraints across heterogeneous information
sources. Achieving the best translation is challenging because sources support different constraints for formulating queries,
and often these constraints cannot be precisely translated. For instance, a query score>8] might be “perfectly” translated
as rating>0.8] at some site, but can only be approximated as grade=A] at another. Unlike other work, our general framework
adopts a customizable “closeness” metric for the translation that combines both precision and recall. Our results show that
for query translation we need to handle interdependencies among both query conjuncts as well as disjuncts. As the basis, we
identify the essential requirements of a rule system for users to encode the mappings for atomic semantic units. Our algorithm
then translates complex queries by rewriting them in terms of the semantic units. We show that, under practical assumptions,
our algorithm generates the best approximate translations with respect to the closeness metric of choice. We also present
a case study to show how our technique may be applied in practice.
Received: 15 October 2000 / Accepted: 15 April 2001 Published online: 28 June 2001 |
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Keywords: | : Constraint-mapping – Approximate query translation – Mediators – Closeness – Information integration |
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