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An Intelligent Automatic Text Summarizer

  • M. Shoaib Jameel
  • Anubhav 
  • Nilesh Singh
  • Nitin Kumar Singh
  • Chingtham Tejbanta Singh
  • M. K. Ghose
Conference paper

Abstract

This paper describes an intelligent text summarizer that summarizes a given piece of text into three different summaries based on three different algorithms. This summarizer uses statistical methods to summarize a text like considering the frequency of words, rare words etc. It then gives a meaningful title to the main text and finally selects the best summary out of a list of given summaries. This summarizer allots the writer a competence level (in written English) after analyzing the text like number of rare words used. The title generator of the summarizer gives a short title to the main text. Results obtained through experiments showed that it is indeed possible to determine the competence level of the writer from the text and proximity of the sentences play a vital role in selecting the best summary.

Keywords

Selection Algorithm Main Text Proper Noun Competence Level Good Summary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Indian Institute of Information Technology, India 2009

Authors and Affiliations

  • M. Shoaib Jameel
    • 1
  • Anubhav 
    • 1
  • Nilesh Singh
    • 1
  • Nitin Kumar Singh
    • 1
  • Chingtham Tejbanta Singh
    • 1
  • M. K. Ghose
    • 1
  1. 1.Dept. of Computer Science and EngineeringSikkim Manipal Institute of TechnologyEast SikkimIndia

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