• DocumentCode
    2864619
  • Title

    Extracting frequent subsequences from a single long data sequence a novel anti-monotonic measure and a simple on-line algorithm

  • Author

    Iwanuma, Koji ; Ishihara, Ryuichi ; Takano, Yo ; Nabeshima, Hidetomo

  • Author_Institution
    Dept. of Comput. Sci. & Media Eng., Yamanashi Univ., Kofu, Japan
  • fYear
    2005
  • fDate
    27-30 Nov. 2005
  • Abstract
    In this paper, we study frequent subsequence extraction from a single very-long data-sequence. First we propose a novel frequency measure, called the total frequency, for counting multiple occurrences of a sequential pattern in a single data sequence. The total frequency is anti-monotonic, and makes it possible to count up pattern occurrences without duplication. Moreover the total frequency has a good property for implementation based on the dynamic programming strategy. Second we give a simple on-line algorithm for a specialized subsequence extraction problem, i.e., a problem with the infinite window-length. This specialized problem is considered to be a relaxation of the general-case problem, thus this fast on-line algorithm is important from the view of practical applications.
  • Keywords
    data mining; antimonotonic measure; frequent subsequence extraction; online algorithm; total frequency measure; Computer science; Data engineering; Data mining; Databases; Dynamic programming; Frequency measurement; Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, Fifth IEEE International Conference on
  • ISSN
    1550-4786
  • Print_ISBN
    0-7695-2278-5
  • Type

    conf

  • DOI
    10.1109/ICDM.2005.60
  • Filename
    1565678