• DocumentCode
    186015
  • Title

    On linguistic-based clustering

  • Author

    Sugawara, Akira ; Kinoshita, Naohiko ; Endo, Yuta

  • Author_Institution
    Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba, Japan
  • fYear
    2014
  • fDate
    22-24 Oct. 2014
  • Firstpage
    265
  • Lastpage
    270
  • Abstract
    Clustering which is one of data mining techniques is a method automatically classifying data into some clusters. Various types of clustering methods based on mathematical models are proposed. We call these methods model-based clustering. We use clustering methods to know data structure. However, we do not know which methods we should select unless we know data structure. Therefore, we propose a new clustering method based on linguistic rules, that is, fuzzy reasoning. We call the new method linguistic-based clustering. It is available when we do not even know data structure. Moreover, the effectiveness is shown through numerical examples.
  • Keywords
    computational linguistics; data mining; data structures; fuzzy reasoning; pattern classification; data classification; data mining techniques; data structure; fuzzy reasoning; linguistic rules; linguistic-based clustering; mathematical models; model-based clustering; Clustering methods; Couplings; Data structures; Fuzzy reasoning; Indexes; Method of moments; Niobium; clustering; fuzzy reasoning; linguistic-based clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2014 IEEE International Conference on
  • Conference_Location
    Noboribetsu
  • Type

    conf

  • DOI
    10.1109/GRC.2014.6982847
  • Filename
    6982847