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Searching association rules based on purchase history and usage-time of an item

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2020, 16(1), pp.81-88
  • DOI : 10.29056/jsav.2020.06.09
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : May 29, 2020
  • Accepted : June 19, 2020
  • Published : June 30, 2020

Lee Bong Kyu 1

1제주대학교

Candidate

ABSTRACT

Various methods of differentiating and servicing digital content for individual users have been studied. Searching for association rules is a very useful way to discover individual preferences in digital content services. The Apriori algorithm is useful as an association rule extractor using frequent itemsets. However, the Apriori algorithm is not suitable for application to an actual content service because it considers only the reference count of each content. In this paper, we propose a new algorithm based on the Apriori that searches association rules by using purchase history and usage-time for each item. The proposed algorithm utilizes the usage time with the weight value according to purchase items. Thus, it is possible to extract the exact preference of the actual user. We implement the proposed algorithm and verify the performance through the actual data presented in the actual content service system.

Citation status

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