• DocumentCode
    2142716
  • Title

    Incrementally Mining High Utility Itemsets in Dynamic Databases

  • Author

    Lin, Chun-Wei ; Hong, Tzung-Pei ; Lan, Guo-Cheng ; Chen, Hsin-Yi ; Kao, Hung-Yu

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2010
  • fDate
    14-16 Aug. 2010
  • Firstpage
    303
  • Lastpage
    307
  • Abstract
    Utility mining is proposed to consider additional measures, such as profits or costs according to user preference. In the past, a two-phase mining algorithm was proposed for fast discovering high utility itemsets from databases. In this paper, an incremental mining algorithm to efficiently update high utility itemsets is proposed for record insertion. Experimental results also show that the proposed algorithm executes faster than the two-phase batch mining algorithm.
  • Keywords
    data mining; database management systems; dynamic databases; incremental mining; two-phase batch mining algorithm; user preference; utility itemsets; Algorithm design and analysis; Association rules; Computer science; Conferences; Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2010 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-7964-1
  • Type

    conf

  • DOI
    10.1109/GrC.2010.151
  • Filename
    5575938