• DocumentCode
    2084061
  • Title

    Improved apriori algorithm based on selection criterion

  • Author

    Vaithiyanathan, V. ; Rajeswari, K. ; Phalnikar, Rashmi ; Tonge, S.

  • Author_Institution
    Sch. of Comput., SASTRA Univ., Tanjore, India
  • fYear
    2012
  • fDate
    18-20 Dec. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Association rule mining is used to uncover closely related item sets in transactions for deciding business policies. Apriori algorithm is widely adopted is association rule mining for generating closely related item sets. Traditional apriori algorithm is space and time consuming since it requires repeated scanning of whole transaction database. In this paper we propose improved apriori algorithm based on compressed transaction database. Transaction database is compressed based on the consequence of interest.
  • Keywords
    business data processing; data mining; database management systems; apriori algorithm; association rule mining; business policy; closely related item set generation; compressed transaction database; selection criterion; Apriori; Association rule mining; Improved Apriori;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence & Computing Research (ICCIC), 2012 IEEE International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4673-1342-1
  • Type

    conf

  • DOI
    10.1109/ICCIC.2012.6510229
  • Filename
    6510229
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2084061