• DocumentCode
    3255865
  • Title

    Applying question classification to Yahoo! Answers

  • Author

    Blooma, Mohan John ; Goh, Dion Hoe-Lian ; Chua, Alton Yeow Kuan ; Ling, Zhiquan

  • Author_Institution
    Wee Kim Wee Sch. of Commun. & Inf., Nanyang Technol. Univ., Singapore
  • fYear
    2008
  • fDate
    4-6 Aug. 2008
  • Firstpage
    229
  • Lastpage
    234
  • Abstract
    Question classification is an important part in modern Question Answering systems. Most approaches to question classification are based on handcrafted rules. Recent studies classify simple questions using machine learning techniques and recommends SVM as on of the best performing classifiers. This study applies a hierarchical classifier based on the SVM machine learning algorithm on questions posed by users, drawn from Yahoo! Answers. The significance of this study is that we attempted to directly classify complex questions with multiple sentence questions posed by real users. We report the accuracy achieved using both a coarse-grained classifier and fine-grained classifier to illustrate the effectiveness of our approach on complex questions. We also present a confusion matrix to analyze the results made by our classifier.
  • Keywords
    Internet; information retrieval; learning (artificial intelligence); natural language processing; pattern classification; support vector machines; Question Answering systems; Yahoo! Answers; hierarchical classifier; machine learning; question classification; support vector machine; Books; Internet; Machine learning; Machine learning algorithms; Natural language processing; Natural languages; Software libraries; Support vector machine classification; Support vector machines; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Digital Information and Web Technologies, 2008. ICADIWT 2008. First International Conference on the
  • Conference_Location
    Ostrava
  • Print_ISBN
    978-1-4244-2623-2
  • Electronic_ISBN
    978-1-4244-2624-9
  • Type

    conf

  • DOI
    10.1109/ICADIWT.2008.4664350
  • Filename
    4664350