• DocumentCode
    514955
  • Title

    An Algorithm of Fast Mining Frequent Itemsets Based on Sequence Number

  • Author

    Fang, Gang ; Xu, Jia-liang ; Luo, Wei-min ; Xiong, Jiang

  • Author_Institution
    Coll. of Math & Comput. Sci., Chongqing Three Gorges Univ., Chongqing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    226
  • Lastpage
    229
  • Abstract
    Aiming to redundant candidate itemsets and repeated computing existing in presented mining algorithms, this paper proposes an algorithm of fast mining frequent itemsets based on sequence number. To fast execute double search, the algorithm adopts two methods of generating candidate itemsets, one is down search that generating subsets of non frequent itemsets, another is up search that computing their digital complementary sets. To only scan once database the algorithm uses character of attribute sequence number to compute support. The algorithm deletes repeated l-candidate itemsets generated by (l+1)-non frequent itemsets via locating subsets´ order, and also improves speed of generating candidate itemsets by computing subsets´ digital complementary set. The result of experiment indicates that the algorithm is faster and more efficient than presented algorithms of mining frequent itemsets.
  • Keywords
    data mining; search problems; sequences; set theory; candidate itemsets generation; digital complementary sets computation; double search; fast mining frequent itemsets algorithm; sequence number; Computer science; Computer science education; Data mining; Databases; Desktop publishing; Distributed control; Educational technology; Itemsets; Logic; Tin; digital complementary set; double search; frequent itemsets; locating order; sequence number;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6388-6
  • Electronic_ISBN
    978-1-4244-6389-3
  • Type

    conf

  • DOI
    10.1109/ETCS.2010.534
  • Filename
    5459968