A hybrid recommendation system using trust scores in a social network
- Authors
- Kim, S.-C.; Park, C.-S.; Kim, S.K.
- Issue Date
- Sep-2012
- Keywords
- Collaborative Filtering; Recommendation System; Social Network; Trust scores
- Citation
- Lecture Notes in Electrical Engineering, v.181 LNEE, pp 107 - 112
- Pages
- 6
- Journal Title
- Lecture Notes in Electrical Engineering
- Volume
- 181 LNEE
- Start Page
- 107
- End Page
- 112
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/50277
- DOI
- 10.1007/978-94-007-5076-0_12
- ISSN
- 1876-1100
1876-1119
- Abstract
- Various techniques for personalized recommendation have been studied. One of the most promising such techniques is collaborative filtering (CF). However, CF is unable to produce high quality recommendations when user rating data is lacking or insufficient. To address this sparsity problem of CF systems, this paper proposes a hybrid recommendation system. The proposed system improves recommendation quality by exploiting trust scores between users in a social network. The proposed system overcomes the weakness of CF for sparse user ratings databases and yields better performance than the conventional CF method.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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