Efficient Indexing of Similarity Models with Inequality Symbolic Regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10139515" target="_blank" >RIV/00216208:11320/13:10139515 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/2463372.2463487" target="_blank" >http://dx.doi.org/10.1145/2463372.2463487</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2463372.2463487" target="_blank" >10.1145/2463372.2463487</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Indexing of Similarity Models with Inequality Symbolic Regression
Original language description
The increasing amount of available unstructured content introduced a new concept of searching for information - the content-based retrieval. The principle behind is that the objects are compared based on their content which is far more complex than simple text or metadata based searching. Many indexing techniques arose to provide an efficient and effective similarity searching. However, these methods are restricted to a specific domain such as the metric space model. If this prerequisite is not fulfilled, indexing cannot be used, while each similarity search query degrades to sequential scanning which is unacceptable for large datasets. Inspired by previous successful results, we decided to apply the principles of genetic programming to the area of database indexing. We developed the GP-SIMDEX which is a universal framework that is capable of finding precise and efficient indexing methods for similarity searching for any given similarity data. For this purpose, we introduce the inequal
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE
ISBN
978-1-4503-1963-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
901-908
Publisher name
ACM
Place of publication
NEW YORK
Event location
Amsterdam
Event date
Jul 6, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000321981300113