• DocumentCode
    3363023
  • Title

    From Ambiguous Words to Key-Concept Extraction

  • Author

    Ajgalik, Marius ; Barla, Michal ; Bielikova, Maria

  • Author_Institution
    Fac. of Inf. & Inf. Technol., Slovak Univ. of Technol., Bratislava, Slovakia
  • fYear
    2013
  • fDate
    26-30 Aug. 2013
  • Firstpage
    63
  • Lastpage
    67
  • Abstract
    Automatic acquisition of keywords for given document is still an area of active research. In this paper, we consider shift from keyword-based representation to other perspective on representation of document´s focus in form of key-concepts. The advantage of using concepts over simple words is that concepts, apart from words, are unambiguous. This leads to better understanding of key-concepts than keywords. We present novel method of key-concept extraction, which provides an efficient way of automatic acquisition of key-concepts in machine processing. We evaluate our approach on classification problem, where we compare it to baseline TF-IDF keyword model and present its competitive results. We discuss its potential of its utilisation on the Web.
  • Keywords
    Internet; data acquisition; data structures; document handling; pattern classification; Web; ambiguous words; automatic key-concept acquisition; automatic keyword acquisition; baseline TF-IDF keyword model; classification problem; key-concept extraction; keyword-based representation; machine processing; Accuracy; Computational linguistics; Computers; Data mining; Semantics; Vectors; Web pages; PageRank; TF-IDF; TextRank; concept extraction; concepts; information content; inverse document frequency; term extraction; text classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2013 24th International Workshop on
  • Conference_Location
    Los Alamitos, CA
  • ISSN
    1529-4188
  • Print_ISBN
    978-0-7695-5070-1
  • Type

    conf

  • DOI
    10.1109/DEXA.2013.16
  • Filename
    6621347