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Scalable Similarity Search for Big Data - Challenges and Research Objectives

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00080758" target="_blank" >RIV/00216224:14330/15:00080758 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-16868-5_1" target="_blank" >http://dx.doi.org/10.1007/978-3-319-16868-5_1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-16868-5_1" target="_blank" >10.1007/978-3-319-16868-5_1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Scalable Similarity Search for Big Data - Challenges and Research Objectives

  • Original language description

    Analysis of contemporary Big Data collections require an effective and efficient content-based access to data which is usually unstructured. This first implies a necessity to uncover descriptive knowledge of complex and heterogeneous objects to make themfindable. Second, multimodal search structures are needed to efficiently execute complex similarity queries possibly in outsourced environments while preserving privacy. Four specific research objectives to tackle the challenges are outlined and discussed. It is believed that a relevant solution of these problems is necessary for a scalable similarity search operating on Big Data.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Scalable Information Systems - 5th International Conference

  • ISBN

    9783319168678

  • ISSN

    1867-8211

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    3-12

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Seoul

  • Event date

    Jan 1, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article