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RFM을 활용한 추천시스템 효율화 연구A Study on Improving Efficiency of Recommendation System Using RFM

Other Titles
A Study on Improving Efficiency of Recommendation System Using RFM
Authors
정소라진서훈
Issue Date
2018
Publisher
대한설비관리학회
Keywords
Recommendation System; Collaborative Filtering; RFM Technique; Performance
Citation
대한설비관리학회지, v.23, no.4, pp.57 - 64
Indexed
KCI
OTHER
Journal Title
대한설비관리학회지
Volume
23
Number
4
Start Page
57
End Page
64
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/79229
ISSN
1598-2475
Abstract
User-based collaborative filtering is a method of recommending an item to a user based on the preference of the neighbor users who have similar purchasing history to the target user. User-based collaborative filtering is based on the fact that users are strongly influenced by the opinions of other users with similar interests. Item-based collaborative filtering is a method of recommending an item by comparing the similarity of the user's previously preferred items. In this study, we create a recommendation model using user-based collaborative filtering and item-based collaborative filtering with consumer’s consumption data. Collaborative filtering is performed by using RFM (recency, frequency, and monetary) technique with purchasing data to recommend items with high purchase potential. We compared the performance of the recommendation system with the purchase amount and the performance when applying the RFM method. The performance of recommendation system using RFM technique is better.
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