A collection of classical literatures for newbies (students of Prof. Gao) Updating...
注：文献排序不分先后，建议同一主题先阅读综述，然后按序（年份）阅读。有的不支持外链的出版社可能无法通过贴的PDF地址下载，请自行检索下载地址
[1]. Bobadilla, Jesus, et al. "Recommender systems survey." Knowledge Based Systems (2013): 109-132.
[2]. Lu, Jie, et al. "Recommender system application developments." decision support systems (2015): 12-32.
[1]. Mnih, Andriy, and Ruslan Salakhutdinov. "Probabilistic Matrix Factorization." neural information processing systems (2008): 1257-1264. [PDF]
[2]. Koren, Yehuda, R. Bell, and C. Volinsky. "Matrix Factorization Techniques for Recommender Systems." Computer 42.8(2009):30-37. [PDF]
[3]. Koren, Yehuda. "Collaborative filtering with temporal dynamics." Communications of The ACM 53.4 (2010): 89-97. [PDF]
[1]. Rendle, Steffen, et al. "BPR: Bayesian personalized ranking from implicit feedback." uncertainty in artificial intelligence (2009): 452-461. [PDF]
[2]. Zhao, Tong, Julian Mcauley, and Irwin King. "Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering." conference on information and knowledge management (2014): 261-270. [PDF]
[1]. Rendle, Steffen. "Factorization Machines." international conference on data mining (2010). [PDF]
[2]. Rendle, Steffen, et al. "Fast context-aware recommendations with factorization machines." international acm sigir conference on research and development in information retrieval (2011): 635-644. [PDF]
[1]. Bonnin, Geoffray, and Dietmar Jannach. "Automated generation of music playlists: Survey and experiments." ACM Computing Surveys (CSUR) 47.2 (2015): 26. [PDF]
[2]. Kaminskas, Marius, and F. Ricci. "Contextual music information retrieval and recommendation: State of the art and challenges." Computer Science Review 6.2–3(2012):89-119. [PDF]
[3]. Knees, Peter, and Markus Schedl. "A survey of music similarity and recommendation from music context data." ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 10.1 (2013): 2. [PDF]
[4]. Oramas, Sergio, et al. "Sound and music recommendation with knowledge graphs." ACM Transactions on Intelligent Systems and Technology (TIST) 8.2 (2017): 21. [PDF]
[1]. Tang, J., Hu, X., & Liu, H. (2013). Social recommendation: a review. Social Network Analysis and Mining, 3(4), 1113-1133. [PDF]
[2]. Ma, Hao, et al. "Sorec: social recommendation using probabilistic matrix factorization." Proceedings of the 17th ACM conference on Information and knowledge management. ACM, 2008. [PDF]
[3]. Jamali, Mohsen, and Martin Ester. "A matrix factorization technique with trust propagation for recommendation in social networks." Proceedings of the fourth ACM conference on Recommender systems. ACM, 2010. [PDF]
[1]. Zhang, Shuai, Lina Yao, and Aixin Sun. "Deep learning based recommender system: A survey and new perspectives." arXiv preprint arXiv:1707.07435 (2017). [PDF]
[2]. Cheng, Heng-Tze, et al. "Wide & deep learning for recommender systems." Proceedings of the 1st Workshop on Deep Learning for Recommender Systems. ACM, 2016. [PDF]
[3]. Wang, Hao, Naiyan Wang, and Dit-Yan Yeung. "Collaborative deep learning for recommender systems." Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2015. [PDF]
[1]. 伍之昂, 王有权, and 曹杰. "推荐系统托攻击模型与检测技术." (2014). [PDF] (综述)
[2]. Lam, Shyong K., and John Riedl. "Shilling recommender systems for fun and profit." international world wide web conferences (2004): 393-402. [PDF] (选读)
[3]. Mehta, Bhaskar, and Wolfgang Nejdl. "Unsupervised strategies for shilling detection and robust collaborative filtering." User Modeling and User-adapted Interaction (2009): 65-97. [PDF]
[4]. Wu, Zhiang, et al. "HySAD: a semi-supervised hybrid shilling attack detector for trustworthy product recommendation." knowledge discovery and data mining (2012): 985-993. [PDF]
[1]. Ye, Junting, and Leman Akoglu. "Discovering opinion spammer groups by network footprints." Joint European Conference on Machine Learning and Knowledge Discovery in Databases (2015): 267-282. [PDF]
[1]. Benevenuto, Fabrício, et al. "Detecting spammers and content promoters in online video social networks." Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (2009):620-627. [PDF]
[2]. Benevenuto, Fabricio, et al. "Detecting spammers on twitter." Collaboration, electronic messaging, anti-abuse and spam conference (CEAS). Vol. 6. (2010):12. [PDF]
[1]. 涂存超, 杨成, 刘知远, & 孙茂松. (2017). 网络表示学习综述. 科学通报, 43, 1681. [PDF]
[2]. Goyal, Palash, and E. Ferrara. "Graph Embedding Techniques, Applications, and Performance: A Survey." (2017). [PDF]
[3]. Cai, Hongyun, Vincent W. Zheng, and Kevin Chen-Chuan Chang. "A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications." arXiv preprint arXiv:1709.07604 (2017). [PDF]
[4]. Perozzi, Bryan, Rami Alrfou, and Steven Skiena. "DeepWalk: online learning of social representations." knowledge discovery and data mining (2014): 701-710. [PDF]
[5]. Tang, Jian, et al. "LINE: Large-scale Information Network Embedding." international world wide web conferences (2015): 1067-1077.
[PDF]
[6]. Grover, Aditya, and Jure Leskovec. "node2vec: Scalable Feature Learning for Networks." knowledge discovery and data mining (2016): 855-864. [PDF]
[1]. Shi, Chuan, et al. "A survey of heterogeneous information network analysis." IEEE Transactions on Knowledge and Data Engineering 29.1 (2017): 17-37.[PDF]
[2]. Shi, Chuan, and S. Yu Philip. "Recommendation with Heterogeneous Information." Heterogeneous Information Network Analysis and Applications. Springer International Publishing, 2017. 97-141. [PDF]
[1]. 任晓龙, and 吕琳媛. "网络重要节点排序方法综述." 科学通报 59.13 (2014): 1175-1197. [PDF]
[2]. Lü, Linyuan, et al. "The H-index of a network node and its relation to degree and coreness." Nature communications 7 (2016): 10168. [PDF]
[3]. Lü, Linyuan, et al. "Vital nodes identification in complex networks." Physics Reports 650 (2016): 1-63. [PDF]