• DocumentCode
    555123
  • Title

    Clustering method and its formalization

  • Author

    Ji Dan ; Qiu Jianlin ; Chen Yanyun ; Chen Li

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Nantong Univ., Nantong, China
  • Volume
    1
  • fYear
    2011
  • fDate
    20-22 Aug. 2011
  • Firstpage
    57
  • Lastpage
    61
  • Abstract
    Clustering method is an important research technology in data mining, and it has a widely use in our life. This paper will describe some traditional algorithms according to different clustering classification, and point out their advantages and shortcomings. Meanwhile, this paper will summarize the concept of formalization, and introduce several common formal specification languages. After applying the predicate logic language with the real example, we can describe the traditional clustering algorithms like k-means, validate the correctness of method itself, and provide a new research idea for algorithms´ examination and innovation.
  • Keywords
    data mining; formal concept analysis; formal specification; pattern classification; pattern clustering; algorithm examination; clustering classification; data mining; formal specification language; formalization concept; formalization method; k-means algorithm; predicate logic language; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Clustering methods; Computers; Data mining; Partitioning algorithms; clustering; data mining; formalization; predicate logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-8622-9
  • Type

    conf

  • DOI
    10.1109/ITAIC.2011.6030150
  • Filename
    6030150