• DocumentCode
    2796454
  • Title

    Incrementally fast updated sequential pattern trees

  • Author

    Hong, Tzung-Pei ; Chen, Hsin-Yi ; Lin, Chun-Wei ; Li, Sheng-Tun

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung
  • Volume
    7
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    3991
  • Lastpage
    3996
  • Abstract
    In the past, the FUFP-tree maintenance algorithm is proposed to efficiently handle the association rules in incremental mining. In this paper, we attempt to modify the FUFP-tree maintenance algorithm for maintaining sequential patterns based on the concept of pre-large sequences to reduce the need for rescanning original databases in incremental mining. A fast updated sequential pattern trees (FUSP trees) structure and the maintenance algorithm are proposed, which makes the tree update process become easier. It does not require rescanning original customer sequences until the accumulative amount of newly added customer sequences exceed a safety bound, which depends on database size. The proposed approach thus becomes efficiently and effectively for handling newly added customer sequences.
  • Keywords
    data mining; tree data structures; FUSP-tree maintenance algorithm; association rules; fast updated frequent pattern tree; fast updated sequential pattern trees; incremental mining; Association rules; Computer science; Cybernetics; Data mining; Electronic mail; Information management; Machine learning; Machine learning algorithms; Transaction databases; Tree data structures; Data mining; FUSP tree; incremental mining; large sequence; pre-large sequence; sequential pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4621100
  • Filename
    4621100