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Automatic Keyphrase Extraction based on NLP and Statistical Methods

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F11%3A43898625" target="_blank" >RIV/49777513:23520/11:43898625 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic Keyphrase Extraction based on NLP and Statistical Methods

  • Original language description

    In this article we would like to present our experimental approach to automatic keyphrases extraction based on statistical methods and Wordnet-based pattern evaluation. Automatic keyphrases are important for automatic tagging and clustering because manually assigned keyphrases are not sufficient in most cases. Keyphrase candidates are extracted in a new way derived from a combination of graph methods (TextRank) and statistical methods (TF*IDF).

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    DATESO 2011

  • ISBN

    978-80-248-2391-1

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    140-145

  • Publisher name

    VŠB Ostrava

  • Place of publication

    Ostrava

  • Event location

    Písek

  • Event date

    Apr 20, 2011

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article