On Fuzzy vs. metric similarity search in complex databases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A10109181" target="_blank" >RIV/00216208:11320/09:10109181 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
On Fuzzy vs. metric similarity search in complex databases
Original language description
The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. For a long time, the database-oriented applications of similarity search employed the definition of similarity restricted to metric distances. Due to the metric postulates (reflexivity, non-negativity, symmetry and triangle inequality), a metric similarity allows to build a metric index above the database which can be subsequently used for efficient (fast) similarity search. On the other hand, the metric postulates limit the domain experts (providers of the similarity measure) in similarity modeling. In this paper we propose an alternative non-metric method of indexing for efficient similarity search. The requirement on metric is replaced by the requirement on fuzzy similarity satisfying the transitivity property with a tuneable fuzzy conjunctor. We also show a duality between the fuzzy approach and the metric one.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN
0302-9743
e-ISSN
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Volume of the periodical
2009
Issue of the periodical within the volume
5822
Country of publishing house
DE - GERMANY
Number of pages
12
Pages from-to
64-75
UT code for WoS article
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EID of the result in the Scopus database
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