A Correlative Denoising Autoencoder to Model Social Influence for Top-N Recommender System

Ma H, Yang H X, Lyu M R, King I. Sorec: social recommendation using probabilistic matrix factorization. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, New York, 2008. 931–940

2008

Earlier work this paper cites.

Hofmann T, Schölkopf B, Smola A J. Kernel methods in machine learning. The Annals of Statistics, 2008, 36: 1171-1220

2008

Earlier work this paper cites.

Vincent P, Larochelle H, Bengio Y, Manzagol P A. Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th International Conference on Machine Learning, New York, 2008. 1096–1103

2008

Earlier work this paper cites.

Liu N N, Yang Q. Eigenrank: a ranking-oriented approach to collaborative filtering. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Singapore, 2008. 83–90

2008

Earlier work this paper cites.

Koren Y. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2008. 426–434

2008

Earlier work this paper cites.

Koren Y, Bell R, Volinsky C. Matrix factorization techniques for recommender systems. Computer, 2009, 42: 30-37

2009

Earlier work this paper cites.

Rendle S, Balby Marinho L, Nanopoulos A, Schmidt-Thieme L. Learning optimal ranking with tensor factorization for tag recommendation. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2009. 727–736

2009

Earlier work this paper cites.

Jamali M, Ester M. A matrix factorization technique with trust propagation for recommendation in social networks. In: Proceedings of the Fourth ACM Conference on Recommender Systems, New York, 2010. 135–142

2010

Earlier work this paper cites.

Ma H, Zhou T C, Lyu M R, King I. Improving recommender systems by incorporating social contextual information. ACM Transactions on Information Systems (TOIS), 2011, 29: 9

2011

Earlier work this paper cites.

Jiang M, Cui P, Liu R, Yang Q, Wang F, Zhu W W, Yang S Q. Social contextual recommendation. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Maui, 2012. 45–54

2012

Earlier work this paper cites.

Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems 25, Lake Tahoe, 2012. 1097–1105

2012

Earlier work this paper cites.

Tang J L, Gao H J, Liu H, Das Sarma A. Etrust: understanding trust evolution in an online world. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, 2012. 253–261

2012

Earlier work this paper cites.

Yang B, Lei Y, Liu D Y, Liu J M. Social collaborative filtering by trust. In: Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, Beijing, 2013. 2747–2753

2013

Earlier work this paper cites.

Pan W K, Chen L. Gbpr: group preference based bayesian personalized ranking for one-class collaborative filtering. In: Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, Beijing, 2013. 2691–2697

2013

Earlier work this paper cites.

Yao W L, He J, Huang G G, Zhang Y C. Modeling dual role preferences for trust-aware recommendation. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, New York, 2014. 975–978

2014

Earlier work this paper cites.

Kalchbrenner N, Grefenstette E, Blunsom P. A convolutional neural network for modelling sentences. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, 2014. 655–665

2014

Earlier work this paper cites.

Zhao T, McAuley J L, King I. Leveraging social connections to improve personalized ranking for collaborative filtering. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, New York, 2014. 261–270

2014

Cited alongside, same era.

Guo G B, Zhang J, Yorke-Smith N. Trustsvd: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial, Austin, 2015. 123–129

2015

Cited alongside, same era.

Sedhain S, Menon A K, Sanner S, Xie L X. Autorec: autoencoders meet collaborative filtering. In: Proceedings of the 24th International Conference on World Wide Web, New York, 2015. 111–112

2015

Cited alongside, same era.

Wang H, Wang N Y, Yeung D Y. Collaborative deep learning for recommender systems. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2015. 1235–1244

2015

Deng S, Huang L, Xu G, Wu X, Wu Z. On deep learning for trust-aware recommendations in social networks. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28: 1164-1177

2017

Closest in time.

Zhang Y F, Ai Q Y, Chen X, Croft W B. Joint representation learning for top-n recommendation with heterogeneous information sources. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, New York, 2017. 1449–1458

2017

Closest in time.

Zhou Y, He F Z, Qiu Y M. Dynamic strategy based parallel ant colony optimization on gpus for tsps. Science China Information Sciences, 2017, 60: 068102

2017

Closest in time.

Chen Y L, He F Z, Wu Y Q, Hou N. A local start search algorithm to compute exact hausdorff distance for arbitrary point sets. Pattern Recognition, 2017, 67: 139-148

2017

Closest in time.