Computer Science ›› 2019, Vol. 46 ›› Issue (1): 126-130.doi: 10.11896/j.issn.1002-137X.2019.01.019
• CCDM2018 • Previous Articles Next Articles
ZENG Xu-yu1,2, YANG Yan1,2, WANG Shu-ying1, HE Tai-jun1, CHEN Jian-bo1
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[1]YANG B,ZHAO P F.Recommended algorithm review[J].Journal of Shanxi University(Natural Science Edition),2011,34(3):337-350.(in Chinese)<br /> 杨博,赵鹏飞.推荐算法综述[J].山西大学学报(自然科学版),2011,34(3):337-350.<br /> [2]SHI Y,LARSON M,HANJALIC A.Collaborative filtering beyond the user-item matrix:A survey of the state of the art and future challenges[J].ACM Computing Surveys (CSUR),2014,47(1):1-45.<br /> [3]MNIH A,SALAKHUTDINOV R R.Probabilistic matrix factorization[C]//Advances in Neural Information Processing ystems 20(NIPS 2007).2008:1257-1264.<br /> [4]LANG K.Newsweeder:Learning to filter netnews[C]//Machine Learning Proceedings.1995:331-339.<br /> [5]KOREN Y,BELL R,VOLINSKY C.Matrix factorization techniques for recommender systems[J].Computer,2009,42(8):30-37.<br /> [6]SHI Y,LARSON M,HANJALIC A.Collaborative filtering beyond the user-item matrix:A survey of the state of the art and future challenges[J].ACM Computing Surveys (CSUR),2014,47(1):3.<br /> [7]SUN Z J,XUE L,XU Y M,et al.Review of deep learning research[J].Application Research of Computers,2012,29(8):2806-2810.(in Chinese)<br /> 孙志军,薛磊,许阳明,等.深度学习研究综述[J].计算机应用研究,2012,29(8):2806-2810.<br /> [8]SALAKHUTDINOV R,MNIH A,HINTON G.Restricted Boltzmann machines for collaborative filtering[C]//Proceedings of the 24th International Conference on Machine Learning.ACM,2007:791-798.<br /> [9]CHILIGUANO P,FAZEKAS G.Hybrid music recommender using content-based and social information[C]//2016 IEEE International Conference on Acoustics,Speech and Signal Proces-sing (ICASSP).IEEE,2016:2618-2622.<br /> [10]KIM D,PARK C,OH J,et al.Convolutional matrix factorization for document context-aware recommendation[C]//Proceedings of the 10th ACM Conference on Recommender Systems.ACM,2016:233-240.<br /> [11]WANG H Y,DONG M W.Latent group recommendation based on dynamic probabilistic matrix factorization model integrated with CNN[J].Journal of Computer Research and Development,2017,54(8):1853-1863.(in Chinese)<br /> 王海艳,董茂伟.基于动态卷积概率矩阵分解的潜在群组推荐[J].计算机研究与发展,2017,54(8):1853-1863.<br /> [12]ADOMAVICIUS G,TUZHILIN A.Toward the next generation of recommender systems:A survey of the state-of-the-art and possible extensions[J].IEEE Transactions on Knowledge and Data Engineering,2005,17(6):734-749.<br /> [13]D’ADDIO R M,MANZATO M G.A sentiment-based item description approach for kNN collaborative filtering[C]//Procee-dings of the 30th Annual ACM Symposium on Applied Computing.ACM,2015:1060-1065.<br /> [14]POLAT H,DU W.SVD-based collaborative filtering with privacy[C]//Proceedings of the 2005 ACM Symposium on Applied Computing.ACM,2005:791-795.<br /> [15]SALAKHUTDINOV R,MNIH A.Bayesian probabilistic matrix factorization using Markov chain Monte Carlo[C]//Proceedings of the 25th International Conference on Machine Learning.ACM,2008:880-887.<br /> [16]LI J,BIOUCAS-DIAS J M,PLAZA A.Collaborative nonnegative matrix factorization for remotely sensed hyperspectral unmixing[C]//2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).IEEE,2012:3078-3081.<br /> [17]BALDI P.Autoencoders,unsupervised learning,and deep architectures[C]//Proceedings of ICML Workshop on Unsupervised and Transfer Learning.JMLR.org,2012:37-49.<br /> [18]KINGMA D P,WELLING M.Auto-encoding variational bayes[J].arXiv preprint arXiv:1312.6114,2013.<br /> [19]SEDHAIN S,MENON A K,SANNER S,et al.Autorec:Autoencoders meet collaborative filtering[C]//Proceedings of the 24th International Conference on World Wide Web.ACM,2015:111-112.<br /> [20]LI S,KAWALE J,FU Y.Deep collaborative filtering via marginalized denoising auto-encoder[C]//Proceedings of the 24th ACM International on Conference on Information and Know-ledge Management.ACM,2015.<br /> [21]WANG H,SHI X,YEUNG D Y.Relational Stacked Denoising Autoencoder for Tag Recommendation[C]//Twenty-Ninth AAAI Conference on Artificial Intellgience.AAAI Press,2015:3052-3058.<br /> [22]WANG C,BLEI D M.Collaborative topic modeling for recommending scientific articles[C]//Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2011:448-456.<br /> [23]WANG H,WANG N,YEUNG D Y.Collaborative deep learning for recommender systems[C]//Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2015:1235-1244. |
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