Seamlessly integrating similarity queries in SQL

Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query langua...

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Veröffentlicht in:Software, practice & experience practice & experience, 2009-03, Vol.39 (4), p.355-384
Hauptverfasser: Barioni, M. C. N., Razente, H. L., Traina, A. J. M., Traina Jr, C.
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Sprache:eng
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content-based retrieval
metric access methods
similarity queries
SQL extension
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container_start_page 355
container_title Software, practice & experience
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creator Barioni, M. C. N.
Razente, H. L.
Traina, A. J. M.
Traina Jr, C.
description Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBMS. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright © 2008 John Wiley & Sons, Ltd.
doi_str_mv 10.1002/spe.898
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subjects content-based retrieval
metric access methods
similarity queries
SQL extension
title Seamlessly integrating similarity queries in SQL
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