• DocumentCode
    174552
  • Title

    Text summarization for Malayalam documents — An experience

  • Author

    Kabeer, Rajina ; Idicula, Sumam Mary

  • Author_Institution
    Dept. of Comput. Sci., Cochin Univ. of Sci. & Technol., Kochi, India
  • fYear
    2014
  • fDate
    26-28 Aug. 2014
  • Firstpage
    145
  • Lastpage
    150
  • Abstract
    The amount of data available in the internet is increasing at a very high speed. Text summarization has helped in making a better use of the information available online. Various methods were adopted to automate text summarization. However there is no existing system for summarizing Malayalam documents. In this paper we have investigated on developing efficient and effective methods to summarize Malayalam documents. This paper explains a statistical sentence scoring technique and a semantic graph based technique for text summarization.
  • Keywords
    Internet; text analysis; Internet; Malayalam documents; semantic graph; statistical sentence scoring; text summarization; Data mining; Dictionaries; Feature extraction; Hidden Markov models; Object recognition; Semantics; Tagging; Sentence scoring; clause; keyword; object; predicate; semantic graph; semantic triples; sentence generation; sub graph; subject; suffix; tagging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Science & Engineering (ICDSE), 2014 International Conference on
  • Conference_Location
    Kochi
  • Print_ISBN
    978-1-4799-6870-1
  • Type

    conf

  • DOI
    10.1109/ICDSE.2014.6974627
  • Filename
    6974627