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Recommender Systems using SVD with Social Network Information
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Min-Gun Kim (Ucess Partners)
Kyoung-jae Kim (Dongguk University_Seoul)
Vol. 22, No. 4, Page: 1 ~ 18
http://dx.doi.org/10.13088/jiis.2016.22.4.001
Keywords
Recommender systems, Social network information, Collaborative filtering, Singular value decomposition, Business analytics
Abstract
Collaborative Filtering (CF) predicts the focal user’s preference for particular item based on user’s preference rating data and recommends items for the similar users by using them. It is a popular technique for the personalization in e-commerce to reduce information overload. However, it has some limitations including sparsity and scalability problems. In this paper, we use a method to integrate social network information into collaborative filtering in order to mitigate the sparsity and scalability problems which are major limitations of typical collaborative filtering and reflect the user's qualitative and emotional information in recommendation process. In this paper, we use a novel recommendation algorithm which is integrated with collaborative filtering by using Social SVD++ algorithm which considers social network information in SVD++, an extension algorithm that can reflect implicit information in singular value decomposition (SVD). In particular, this study will evaluate the performance of the model by reflecting the real-world user's social network information in the recommendation process.
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사회연결망정보를 고려하는 SVD 기반 추천시스템
김민건 (유세스파트너(주))
김경재 (동국대학교_서울_경영대학 경영정보학과)
Keywords
추천시스템, 사회연결망정보, 협업필터링, 특이값 분해, 비즈니스 애널리틱스
Abstract
협업필터링은 사용자의 선호도 평가자료를 이용하여 특정 사용자의 특정 상품에 대한 선호도를 예측하고 이를 이용하여 유사한 사용자에게 상품을 추천한다. 협업필터링은 전자상거래에서의 정보 과잉현상을 줄여 주기에 가장 인기 있는 개인화 기법이다. 그러나 협업필터링은 희소성과 확장성 문제등을 가지고 있다. 본 연구에서는 희소성과 확장성 문제와 같은 협업필터링의 주요 한계점을 보완하고추천과정에 사용자의 정성적이고 감성적인 정보를 반영하도록 하기 위하여 사회연결망 정보와 협업필터링을 접목하는 방안을 이용한다. 본 논문에서는 특이값 분해에 내재적인 정보를 반영할 수 있도록확장한 SVD++에 사회연결망 정보를 고려할 수 있도록 한 Social SVD++ 알고리듬을 협업필터링에 접목한 새로운 추천 알고리듬을 이용한다. 특히, 본 연구는 추천과정에 실제 사용자의 사회연결망 정보를 반영하여 모형의 성과를 평가할 것이다.
Cite this article
JIIS Style
Kim, M.-G., and K.-j. Kim, "Recommender Systems using SVD with Social Network Information", Journal of Intelligence and Information Systems, Vol. 22, No. 4 (2016), 1~18.

IEEE Style
Min-Gun Kim, and Kyoung-jae Kim, "Recommender Systems using SVD with Social Network Information", Journal of Intelligence and Information Systems, vol. 22, no. 4, pp. 1~18, 2016.

ACM Style
Kim, M.-G., and Kim, K.-j., 2016. Recommender Systems using SVD with Social Network Information. Journal of Intelligence and Information Systems. 22, 4, 1--18.
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@article{Kim:JIIS:2016:665,
author = {Kim, Min-Gun and Kim, Kyoung-jae},
title = {Recommender Systems using SVD with Social Network Information},
journal = {Journal of Intelligence and Information Systems},
issue_date = {December 2016},
volume = {22},
number = {4},
month = Dec,
year = {2016},
issn = {2288-4866},
pages = {1--18},
url = {http://dx.doi.org/http://dx.doi.org/10.13088/jiis.2016.22.4.001 },
doi = {http://dx.doi.org/10.13088/jiis.2016.22.4.001},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Recommender systems, Social network information, Collaborative filtering, Singular value decomposition and Business analytics },
}
%0 Journal Article
%1 665
%A Min-Gun Kim
%A Kyoung-jae Kim
%T Recommender Systems using SVD with Social Network Information
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 22
%N 4
%P 1-18
%D 2016
%R http://dx.doi.org/10.13088/jiis.2016.22.4.001
%I Korea Intelligent Information System Society