지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2014.1
- 수록면
- 309 - 321 (13page)
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초록· 키워드
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Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.
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참고문헌 (8)
참고문헌 신청
Agrawal, R. / 1994 / Fast Algorithms for Mining Association Rules in Large Databases / Proceedings of the VLDB :487~499
조영성 / 2012 / RFM기법과 k-means 기법을 이용한 개인화 추천시스템의 개발 / 한국컴퓨터정보학회논문지 17(6):163~172
Cho, Y.S. / 2012 / Implementation of Personalized recommendation System using k-means Clustering of Item Category based on RFM / IEEE International Conference on Management of Innovation and Technology Publication
Gunaratne, K.A / 1998 / Globalisation, Decimation of Labour and Strategic Managerial Options / Twelfth Australia and New Zealand Academy of Management International Conference
Herlocker, J.L. / 1999 / An Algorithm Framework for Performing Collaborative Filtering / Proceedings of the 1999 Conference on Research and Development in Information Retrival
조영성 / 2012 / RFM기법과 k-means 기법을 이용한 개인화 추천시스템의 개발 / 한국컴퓨터정보학회논문지 17(6):163~172
Cho, Y.S. / 2012 / Implementation of Personalized recommendation System using k-means Clustering of Item Category based on RFM / IEEE International Conference on Management of Innovation and Technology Publication
Gunaratne, K.A / 1998 / Globalisation, Decimation of Labour and Strategic Managerial Options / Twelfth Australia and New Zealand Academy of Management International Conference
Herlocker, J.L. / 1999 / An Algorithm Framework for Performing Collaborative Filtering / Proceedings of the 1999 Conference on Research and Development in Information Retrival
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