{"type":"ScholarlyArticle","title":"Social Collaborative Filtering by Trust","authors":[{"name":"Bo Yang","slug":"bo-yang","given":"Bo","family":"Yang","affiliation":"School of Computer Science and Technology; Department of Computer Science Jilin University , China; Hong Kong Baptist University , Hong Kong"},{"name":"Yu Lei","slug":"yu-lei-2","given":"Yu","family":"Lei","affiliation":"School of Computer Science and Technology; Department of Computer Science Jilin University , China; Hong Kong Baptist University , Hong Kong"},{"name":"Dayou Liu","slug":"dayou-liu","given":"Dayou","family":"Liu","affiliation":"School of Computer Science and Technology; Department of Computer Science Jilin University , China; Hong Kong Baptist University , Hong Kong"},{"name":"Jiming Liu","slug":"jiming-liu","given":"Jiming","family":"Liu","affiliation":"School of Computer Science and Technology; Department of Computer Science Jilin University , China; Hong Kong Baptist University , Hong Kong"}],"abstract":"To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collaborative filtering is one of the most widely adopted recommender algorithms, whereas it is suffering the issues of data sparsity and cold start that will severely degrade quality of recommendations. To address such issues, this article proposes a novel method, trying to improve the performance of collaborative filtering recommendation by means of elaborately integrating twofold sparse information, the conventional rating data given by users and the social trust network among the same users. It is a model-based method adopting matrix factorization technique to map users into low-dimensional latent feature spaces in terms of their trust relationship, aiming to reflect users' reciprocal influence on their own opinions more reasonably. The validations against a real-world dataset show that the proposed method performs much better than state-of-the-art recommendation algorithms for social collaborative filtering by trust.","doi":null,"url":"https://ijcai.org/proceedings/2013/404","pdf":"https://ijcai.org/proceedings/2013/0404.pdf","markdown":"https://ijcai.org/proceedings/2013/404.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/404","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":404,"pages":{"first":2747,"last":2752},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Granovetter, 1973] Mark S. Granovetter. The strength of weak ties. The American Journal of Sociology, 78(6):1360-1380, May 1973.","title":"The strength of weak ties","authors":"Mark S Granovetter","year":"1973","venue":"The American Journal of Sociology","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Jamali and Ester, 2010] Mohsen Jamali and Martin Ester. A matrix factorization technique with trust propagation for recommendation in social networks. In Proceedings of the Fourth ACM Conference on Recommender Systems, pages 135-142, Barcelona, Spain, September 2010. Association for Computing Machinery.","title":"A matrix factorization technique with trust propagation for recommendation in social networks","authors":"Mohsen Jamali, Martin Ester","year":"2010","venue":"Proceedings of the Fourth ACM Conference on Recommender Systems","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Kautz et al., 1997] Henry Kautz, Bart Selman and Mehul Shah. ReferralWeb: Combining social networks and collaborative filtering. Communications of the ACM, 40(3):63-65, March 1997.","title":"ReferralWeb: Combining social networks and collaborative filtering","authors":"Henry Kautz, Bart Selman, Mehul Shah","year":"1997","venue":"Communications of the ACM","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Ma et al., 2008] Hao Ma, Haixuan Yang, Michael R. Lyu and Irwin King. SoRec: Social recommendation using probabilistic matrix factorization. In Proceedings of the 17th ACM Conference on Information and Knowledge Management, pages 931-940, Napa Valley, California, USA, October 2008. Association for Computing Machinery.","title":"SoRec: Social recommendation using probabilistic matrix factorization","authors":"Hao Ma, Haixuan Yang, Michael R Lyu, Irwin King","year":"2008","venue":"Proceedings of the 17th ACM Conference on Information and Knowledge Management","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Ma et al., 2009] Hao Ma, Irwin King and Michael R. Lyu. Learning to recommend with social trust ensemble. In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 203-210, Boston, Massachusetts, USA, July 2009. Association for Computing Machinery.","title":"Learning to recommend with social trust ensemble","authors":"Irwin Hao Ma, Michael R King, Lyu","year":"2009","venue":"Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Ma et al., 2011] Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu and Irwin King. Recommender systems with social regularization. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, pages 287-296, Hong Kong, China, February 2011. Association for Computing Machinery.","title":"Recommender systems with social regularization","authors":"Hao Ma, Dengyong Zhou, Chao Liu, Michael R Lyu, Irwin King","year":"2011","venue":"Proceedings of the Fourth ACM International Conference on Web Search and Data Mining","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Resnick and Varian, 1997] Paul Resnick and Hal R. Varian. Recommender systems. Communications of the ACM, 40(3):56-58, March 1997.","title":"Recommender systems","authors":"Paul Resnick, Hal R Varian","year":"1997","venue":"Communications of the ACM","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Salakhutdinov and Mnih, 2007] Ruslan Salakhutdinov and Andriy Mnih. Probabilistic matrix factorization. In Proceedings of the 22nd Annual Conference on Advances in Neural Information Processing Systems, pages 1257- 1264, Vancouver, Canada, December 2007. Association for Computing Machinery.","title":"Ruslan Salakhutdinov and Andriy Mnih. Probabilistic matrix factorization","authors":"Mnih Salakhutdinov","year":"2007","venue":"Proceedings of the 22nd Annual Conference on Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Sinha and Swearingen, 2001] Rashmi Sinha and Kirsten Swearingen. Comparing recommendations made by online systems and friends. In Proceedings of the Joint DELOS-NSF Workshop on Personalization and Recommender systems in Digital Libraries, pages 64-69, Dublin, Ireland, June 2001.","title":"Comparing recommendations made by online systems and friends","authors":"Swearingen Sinha, Rashmi Sinha, Kirsten Swearingen","year":"2001","venue":"Proceedings of the Joint DELOS-NSF Workshop on Personalization and Recommender systems in Digital Libraries","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Yang et al., 2012] Bo Yang, Pengfei Zhao, Shuqiu Ping and Jing Huang. Improving the recommendation of collaborative filtering by fusing trust network. In Proceedings of the 7th International Conference on Computational Intelligence and Security, pages 195-199, Guangzhou, China, November 2012. Institute of Electrical and Electronics Engineers.","title":"Improving the recommendation of collaborative filtering by fusing trust network","authors":"Bo Yang, Pengfei Zhao, Shuqiu Ping, Jing Huang","year":"2012","venue":"Proceedings of the 7th International Conference on Computational Intelligence and Security","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Zhou et al., 2008] Yunhong Zhou, Dennis Wilkinson, Robert Schreiber and Rong Pan. Large-scale parallel collaborative filtering for the Netflix prize. In Proceedings of 4th International Conference on Algorithmic Aspects in Information and Management, pages 337-348, Shanghai, China, June 2008. Springer-Verlag.","title":"Large-scale parallel collaborative filtering for the Netflix prize","authors":"Yunhong Zhou, Dennis Wilkinson, Robert Schreiber, Rong Pan","year":"2008","venue":"Proceedings of 4th International Conference on Algorithmic Aspects in Information and Management","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Ziegler and Lausen, 2004] Cai N. Ziegler and Georg Lausen. Analyzing correlation between trust and user similarity in online communities. In Proceedings of the Second International Conference on Trust Management, Page 251-265, Oxford, UK, March 2004. Springer-Verlag.","title":"Analyzing correlation between trust and user similarity in online communities","authors":"N Cai, Georg Ziegler, Lausen","year":"2004","venue":"Proceedings of the Second International Conference on Trust Management","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}