• DocumentCode
    3696922
  • Title

    A k-Highest Expert Text Classification Algorithm Based on Choquet Integral

  • Author

    Shuchao Feng;Wenqian Shang;Yuqi Wang

  • Author_Institution
    Sch. of Sci., Commun. Univ. of China, Beijing, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    499
  • Lastpage
    503
  • Abstract
    In recent years, the research on text classification algorithm is still a hot topic in text mining. The KNN is a classic text classification algorithm. The rule of finding the nearest neighbors directly affects the performance and precision of categorization. In this paper, we mainly focus on distance measure and similarity. We propose a new text classification algorithm which combines KNN and Choquet integral. Choquet integral provides a new way to find the k-nearest neighbors. The result of experiment shows that the performance of this method is better than the classical distance measure or similarity measure.
  • Keywords
    "Text categorization","Training","Classification algorithms","Measurement","Computer science","Q-factor","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence (ACIT-CSI), 2015 3rd International Conference on
  • Type

    conf

  • DOI
    10.1109/ACIT-CSI.2015.95
  • Filename
    7336115