• DocumentCode
    1614302
  • Title

    The Research of kNN Text Categorization Algorithm Based on Eager Learning

  • Author

    Dong, Tao ; Cheng, Weinan ; Shang, Wenqian

  • Author_Institution
    Sch. of Comput., Commun. Univ. of China, Beijing, China
  • fYear
    2012
  • Firstpage
    1120
  • Lastpage
    1123
  • Abstract
    Text categorization is a fundamental methodology of text mining and it is also a hot topic of the research of data mining and web mining in recent years. It plays an important role in business, government decision-making management, scientific research, and so on. This paper presents an improved algorithm of text categorization which combines eager learning with kNN classification. Experimental results show that the improved algorithm not only improve the efficiency of categorization, but also significantly increase the accuracy of categorization and produce a qualitative leap on the practical value of the sensitive information system.
  • Keywords
    Internet; data mining; learning (artificial intelligence); pattern classification; security of data; text analysis; Web mining; data mining; eager learning; kNN classification; kNN text categorization algorithm; sensitive information system; text mining; Algorithm design and analysis; Computational modeling; Computers; Educational institutions; Text categorization; Training; Vectors; Eager learning; Text categorization; kNN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-1450-3
  • Type

    conf

  • DOI
    10.1109/ICICEE.2012.297
  • Filename
    6322586