DIGITAL LIBRARY ARCHIVE
HOME > DIGITAL LIBRARY ARCHIVE
< Previous   List   Next >  
Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering
Full-text Download
Yeong-Bin Cho (Department of Business Administration, Konkuk University)
Yoon-Ho Cho (School of Business Administration, Kookmin University)
Vol. 13, No. 2, Page: 69 ~ 80
Keywords
Recommender systems, Purchase sequence, Collaborative Filtering, Association Rules
Abstract
The preferences of customers change over time. However, existing collaborative filtering (CF) systems are static, since they only incorporate information regarding whether a customer buys a product during a certain period and do not make use of the purchase sequences of customers. Therefore, the quality of the recommendations of the typical CF could be improved through the use of information on such sequences. In this study, we propose a new methodology for enhancing the quality of CF recommendation that uses customer purchase sequences. The proposed methodology is applied to a large department store in Korea and compared to existing CF techniques. Various experiments using real-world data demonstrate that the proposed methodology provides higher quality recommendations than do typical CF techniques with better performance.
Show/Hide Detailed Information in Korean
구매순서를 고려한 개선된 협업필터링 방법론
조영빈 (건국대학교 사회과학대학 경영학과)
조윤호 (국민대학교 경영학부)
Abstract
고객의 선호도는 시간에 따라 변화하지만 기존 협업필터링기법(Collaborative Filtering : CF)은 정적인 데이터만을 다룬다. 이는 기존 CF 기법이 특정 기간 동안 고객의 구매 여부만 고려할 뿐 고객의 구매순서를 사용하지 않기 때문이다. 따라서 기존 CF 기법은 고객의 동적인 데이터인 구매순서를 고려함으로써 추천의 품질을 높일 가능성이 있다. 본 연구에서는 고객의 구매순서를 활용함으로써 CF 기법의 추천 품질을 향상시키는 새로운 상품추천 방법론을 제안한다. 즉, 군집분석기법인 자기조직화지도(Self-Organizing Map : SOM)를 활용하여 고객의 구매순서를 파악한 후 연관규칙탐사(Association Rule Mining : ARM)를 사용하여 고객들의 구매순서 중 일정 정도의 통계적인 타당성을 갖는 구매순서 패턴을 찾아내어 이를 추천 시에 활용한다. 대형 백화점의 구매자료에 적용하여 제안한 방법론의 효과성을 실험한 결과 제안한 방법론이 기존 CF 기법보다 우수한 추천품질을 가지고 있음이 실증적으로 확인되었다.
Cite this article
JIIS Style
Cho, Y.-B., and Y.-H. Cho, "Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering", Journal of Intelligence and Information Systems, Vol. 13, No. 2 (2007), 69~80.

IEEE Style
Yeong-Bin Cho, and Yoon-Ho Cho, "Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering", Journal of Intelligence and Information Systems, vol. 13, no. 2, pp. 69~80, 2007.

ACM Style
Cho, Y.-B., and Cho, Y.-H., 2007. Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering. Journal of Intelligence and Information Systems. 13, 2, 69--80.
Export Formats : BiBTeX, EndNote
Advanced Search
Date Range

to
Search
@article{Cho:JIIS:2007:295,
author = {Cho, Yeong-Bin and Cho, Yoon-Ho},
title = {Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering},
journal = {Journal of Intelligence and Information Systems},
issue_date = {June 2007},
volume = {13},
number = {2},
month = Jun,
year = {2007},
issn = {2288-4866},
pages = {69--80},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Recommender systems, Purchase sequence, Collaborative Filtering and Association Rules },
}
%0 Journal Article
%1 295
%A Yeong-Bin Cho
%A Yoon-Ho Cho
%T Considering Customer Buying Sequences to Enhance the Quality of Collaborative Filtering
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 13
%N 2
%P 69-80
%D 2007
%R
%I Korea Intelligent Information System Society