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가격 비교 서비스에서 상품 그룹 분석을 통한 추천 기법

Title
가격 비교 서비스에서 상품 그룹 분석을 통한 추천 기법
Other Titles
A Recommendation Method Based on Analysis of Item Groups in Price-Comparison Services
Author
김상욱
Keywords
추천; 협업 필터링; 가격 비교 서비스; Cold-start 문제; recommendation; collaborative filtering; price-comparison services; cold-start problem
Issue Date
2013-11
Publisher
한국정보과학회
Citation
정보과학회논문지 컴퓨팅의 실제 및 레터, 2013, 19, P.541-546
Abstract
Many major portal sites provide price-comparison services, allowing the customer to compare prices without visiting individual online shopping malls. Personalized recommendation would aid the customer in this process by recommending items that the customer may find attractive. However, existing methods suffer from the cold-start problem that they cannot produce recommendations or can make low-quality recommendations for users having insufficient records of their activities. To alleviate the problem, this paper proposes recommendation strategies and a graph-based recommendation method for the price-comparison services. We verify the superiority of the proposed method by comparing it with existing recommendation methods using real-world data.
URI
http://www.dbpia.co.kr/Journal/ArticleDetail/NODE02282211http://hdl.handle.net/20.500.11754/50940
ISSN
1229-7712
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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