| [1] Zhou J, Luo T j, Cheng F. Modeling learners and contents in academic-oriented recommendation framework[C]//Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on. IEEE, 2011: 1017-1024.[2] Koren Y. Collaborative filtering with temporal dynamics[C]//Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2009: 447-456.[3] Chen L H. Enhancement of student learning performance using personalized diagnosis and remedial learning system[J]. Computers & Education, 2011, 56(1): 289-299.[4] Klašnja-Mili D? evi D? A, Vesin B, Ivanovi D? M, et al. E-learning personalization based on hybrid recommendation strategy and learning style identification[J]. Computers & Education, 2011, 56(3): 885-899.[5] Tang T Y, McCalla G. Smart Recommendation for an Evolving E-Learning System[C]//Proceedings of the IJCAI Workshop on Machine Learning in Information Filtering. Stockholm, 2003, 86-91.[6] McCalla G. The ecological approach to the design of e-learning environments: purpose-based capture and use of information about learners[J]. Electronic Version, Journal of Interactive media in Education, 2004, 7:1-23.[7] Drachsler H, Hummel H G K, Koper R. Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model[J]. International Journal of Learning Technology, 2008, 3(4): 404-423.[8] Lee J, Lee K, Kim J G. Personalized academic research paper recommendation system[EB/OL].(2013)[2013-03-23]. http://www.cc.gatech.edu/grads/j/jkim693/projects/recommendation.pdf.[9] Gipp B, Beel J, Hentschel C. Scienstein: a research paper recommender system[C]//Proceedings of International Conference on Emerging Trends in Computing. Virudhunagar, India:IEEE 2009: 309-315.[10] Gori M, Pucci A. Research paper recommender systems: a random-walk based approach[C]//Web Intelligence, WI 2006. IEEE/WIC/ACM International Conference on. IEEE, 2006: 778-781.[11] Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions[J]. Knowledge and Data Engineering, IEEE Transactions on, 2005, 17(6): 734-749.[12] Mehta B, Hofmann T, Nejdl W. Robust collaborative filtering//Proceedings of the 2007 ACM conference on Recommender systems. ACM, 2007: 49-56.[13] Rennie J D M, Srebro N. Fast maximum margin matrix factorization for collaborative prediction[C]//Proceedings of the 22nd international conference on Machine learning. ACM, 2005: 713-719.[14] Koren Y. Factorization meets the neighborhood: a multifaceted collaborative filtering model[C]//Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2008: 426-434.[15] Takács G, Pilászy I, Németh B, et al. Major components of the gravity recommendation system[J]. ACM SIGKDD Explorations Newsletter, 2007, 9(2): 80-83.[16] Ding Y, Li X. Time weight collaborative filtering[C]//Proceedings of the 14th ACM international conference on Information and knowledge management. ACM, 2005: 485-492.[17] Zimdars A, Chickering D M, Meek C. Using temporal data for making recommendations//Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence. Morgan Kaufmann Publishers Inc, 2001: 580-588.[18] Lathia N, Hailes S, Capra L. Temporal collaborative filtering with adaptive neighbourhoods[C]//Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval. ACM, 2009: 796-797.[19] Breese J S, Heckerman D, Kadie C. Empirical analysis of predictive algorithms for collaborative filtering[C]//Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence. Morgan Kaufmann Publishers Inc, 1998: 43-52.[20] Sarwar B, Karypis G, Konstan J, et al. Item-based collaborative filtering recommendation algorithms[C]//Proceedings of the 10th international conference on World Wide Web. ACM, 2001: 285-295.[21] Sun J, Tao D, Faloutsos C. Beyond streams and graphs: dynamic tensor analysis[C]//Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2006: 374-383. |
