• DocumentCode
    3337226
  • Title

    Text2arff: Automatic feature extraction software for Turkish texts

  • Author

    Amasyali, M. Fatih ; Davletov, Feruz ; Torayew, Arslan ; Çiftçi, Ümit

  • fYear
    2010
  • fDate
    22-24 April 2010
  • Firstpage
    629
  • Lastpage
    632
  • Abstract
    Which features are the most important for the text classification tasks? In the automatic text categorization area, several studies seek answers to this question. In this paper, a feature extraction tool for Turkish texts (Text2arff) is presented. The toolbox automatically extracts several features such as the frequencies of the words and ngrams, word clustering, Latent semantic indexing etc. The features of the texts are saved in arff (WEKA) file format. The arff files can be used easily with WEKA machine learning library.
  • Keywords
    feature extraction; natural language processing; pattern classification; text analysis; word processing; Turkish; WEKA; arff file format; feature extraction; text categorization; text classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th
  • Conference_Location
    Diyarbakir
  • Print_ISBN
    978-1-4244-9672-3
  • Type

    conf

  • DOI
    10.1109/SIU.2010.5651686
  • Filename
    5651686
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3337226