• DocumentCode
    3276741
  • Title

    The research on topic detection based on multi-models and multi-characteristics

  • Author

    Zhang Su-xiang ; Li Ya-xi ; Wang Xiu-li ; Xie Lin-yan

  • Author_Institution
    State Grid Inf. & Telecommun. Co., Ltd., Beijing, China
  • fYear
    2013
  • fDate
    23-25 May 2013
  • Firstpage
    595
  • Lastpage
    598
  • Abstract
    In this paper, a new approach was proposed for the topic detection, which combined the multi-models and multi-characteristics, entity information similarities were researched as features for support vector machine model (SVM) by us, for example, the content similarity, time similarity and location similarity methods can be proposed respectively, the Bayesian model also can be discussed to obtain the atomic characteristics in this paper. Except this features, the expert knowledge base has been studied to solve the difficult classification problem. The experimental results show that the approach combined the statistical model with expert rule base is effective.
  • Keywords
    Bayes methods; expert systems; information retrieval; support vector machines; text analysis; Bayesian model; SVM; content similarity; entity information similarity; expert knowledge base; expert rule base; location similarity; multicharacteristics; multimodels; statistical model; support vector machine model; time similarity; topic detection; Support vector machine classification; Testing; clustering; entity information similarity; feature selection; support vector model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4673-4997-0
  • Type

    conf

  • DOI
    10.1109/ICSESS.2013.6615379
  • Filename
    6615379