• DocumentCode
    2351029
  • Title

    The Data Scales in Multi-valued Context Based on Formal Concept Analysis

  • Author

    Shao-Chun, Wu ; Ming-Dong, Li ; Yan, Tang ; Ling-Yu, Xu ; Da-Ming, Wei

  • Author_Institution
    Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China
  • Volume
    2
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    278
  • Lastpage
    282
  • Abstract
    Formal Concept Analysis has very important meaning in mathematical methods for data mining and knowledge processing. In the face of the variety of the data structure, traditional methods can hardly meet decider´s need. This paper summarizes a few of data structure for the concept analysis and present the data scale methods for each other based on their own characters. It not only extends the application of the concept analysis, but also makes the data scale methods more efficiently.
  • Keywords
    data analysis; data mining; data structures; formal specification; mathematical analysis; data mining; data scale methods; data structure; formal concept analysis; knowledge processing; multi-valued context; Data engineering; Data mining; Data structures; Information analysis; Information technology; Knowledge engineering; Lattices; Memory; Relational databases; Text analysis; Concept Context; Concept Lattice; Data Scale;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology, 2009. CIT '09. Ninth IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3836-5
  • Type

    conf

  • DOI
    10.1109/CIT.2009.39
  • Filename
    5329084