• DocumentCode
    1780542
  • Title

    Automatic Question Generation system

  • Author

    Pabitha, P. ; Mohana, M. ; Suganthi, S. ; Sivanandhini, B.

  • Author_Institution
    Dept. of Comput. Technol., Anna Univ., Chennai, India
  • fYear
    2014
  • fDate
    10-12 April 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The process of automating the question generation consists of many tasks. Selecting the target content (what to ask), question type (who, why, how) and actual question generation are the major issue of Automatic Question Generation. Certain definitions retrieved is available in Wikipedia either directly or is the outcome of executing set of sub queries for each key phrase categories The problem in the existing system is that some of the definition sentences which are taken out from Wikipedia were implicit. The proposed system overcomes the problems by using Supervised Learning Approach, Naïve Bayes method. It also extends its work to use Summarization, Noun Filtering and Question Generation in the aim of generating semantically correct questions.
  • Keywords
    Bayes methods; Web sites; information filtering; learning (artificial intelligence); query processing; question answering (information retrieval); text analysis; Wikipedia; automatic question generation system; definition sentences; key phrase categories; naïve Bayes method; noun filtering; question type; subqueries; summarization; supervised learning approach; Data mining; Information filters; Information services; Information technology; Market research; Automatic Question Generation; Key phrases; Naïve Bayes; Noun Filtering; Stemming; Summarization; Supervised Machine Learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Trends in Information Technology (ICRTIT), 2014 International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1109/ICRTIT.2014.6996216
  • Filename
    6996216