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Monte Carlo Projective Clustering of Texts

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A00207446" target="_blank" >RIV/00216208:11320/09:00207446 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Monte Carlo Projective Clustering of Texts

  • Original language description

    In this paper we propose a new, improved version of a Monte Carlo projective clustering algorithm ?DOC. DOC was designed for general vector data and we extend it to deal with variable dimension significance and use it in web search snippets clustering. We discuss advantages and weaknesses of our approach with respect to known algorithms.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    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

  • Article name in the collection

    ICSOFT 2009 Proceedings of the 4th International Conference on Software and Data Technologies

  • ISBN

    978-989-674-009-2

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

  • Publisher name

  • Place of publication

  • Event location

    Neuveden

  • Event date

    Jan 1, 2009

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article