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Algorithmic exploration of axiom spaces for efficient similarity search at large scale

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10131930" target="_blank" >RIV/00216208:11320/12:10131930 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007/978-3-642-32153-5_4" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-642-32153-5_4</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-642-32153-5_4" target="_blank" >10.1007/978-3-642-32153-5_4</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Algorithmic exploration of axiom spaces for efficient similarity search at large scale

  • Original language description

    Similarity search is becoming popular in even more disciplines, such as multimedia databases, bioinformatics, social networks, to name a few. The existing indexing techniques often assume the metric space model that could be too restrictive from the domain point of view. Hence, many modern applications that involve complex similarities do not use any indexing and use just sequential search, so they are applicable only to small databases. In this paper we revisit the assumptions which persist in the mainstream research of content-based retrieval. Leaving the traditional indexing paradigms such as the metric space model, our goal is to propose alternative methods for indexing that shall lead to high-performance similarity search. We introduce the designof the algorithmic framework SIMDEX for exploration of analytical properties (axioms) useful for indexing that hold in a given complex similarity space but were not discovered so far. Consequently, the known axioms will be localized as a

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP202%2F11%2F0968" target="_blank" >GAP202/11/0968: Large-scale Nonmetric Similarity Search in Complex Domains</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2012

  • 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

  • ISSN

    0302-9743

  • e-ISSN

  • Volume of the periodical

    7404

  • Issue of the periodical within the volume

    2012

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    14

  • Pages from-to

    40-53

  • UT code for WoS article

  • EID of the result in the Scopus database