• DocumentCode
    3488783
  • Title

    Hybrid search based association rule mining

  • Author

    Ghanem, Ahmed M. ; Sallam, Hamed M.

  • Author_Institution
    Fac. of Eng., Suez Canal Univ., Ismailia, Egypt
  • fYear
    2011
  • fDate
    23-26 Aug. 2011
  • Firstpage
    608
  • Lastpage
    612
  • Abstract
    Association rule mining algorithms provide different search strategies to discover the frequent itemsets; however the problem of large search space is still hard to handle. The present paper suggests a novel hybrid search technique based on reducing the search space, I/O, and CPU times. This can improve the performance up to several orders of magnitude compared to APRIORI algorithm.
  • Keywords
    data mining; search problems; APRIORI algorithm; association rule mining; frequent itemset discovery; hybrid search technique; Algorithm design and analysis; Association rules; Itemsets; Navigation; Search problems; Association Rules; Data Mining; Hybrid Search; Reduced Search Space;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and Signal Processing (PacRim), 2011 IEEE Pacific Rim Conference on
  • Conference_Location
    Victoria, BC
  • ISSN
    1555-5798
  • Print_ISBN
    978-1-4577-0252-5
  • Electronic_ISBN
    1555-5798
  • Type

    conf

  • DOI
    10.1109/PACRIM.2011.6032963
  • Filename
    6032963
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3488783