G. Adomavicius and A. Tuzhilin, Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Trans. Knowl. Data Eng., vol. 17, no. 6, pp. 734-749, 2005.
L. Y. Lü, M. Medo, C. H. Yeung, Y. C. Zhang, Z. K. Zhang, and T. Zhou, Recommender systems, Phys. Rep., vol. 519, no. 1, pp. 1-49, 2012.
G. Linden, B. Smith, and J. York, Amazon.Com recommendations: Item-to-Item collaborative filtering, IEEE Int. Comput., vol. 7, no. 1, pp. 76-80, 2003.
O. Celma and X. Serra, FOAFing the music: Bridging the semantic gap in music recommendation, Web Semant., vol. 6, no. 4, pp. 250-256, 2008.
F. Hopfgartner, T. Brodt, J. Seiler, B. Kille, A. Lommatzsch, M. Larson, R. Turrin, and A. Serény, Benchmarking news recommendations: The CLEF NewsREEL use case, ACM SIGIR Forum, vol. 49, no. 2, pp. 129-136, 2015.
M. Balabanović and Y. Shoham, Combining content-based and collaborative recommendation, Commun. ACM, vol. 40, no. 3, pp. 66-72, 1997.
J. B. Shu, X. X. Shen, H. Liu, B. L. Yi, and Z. L. Zhang, A content-based recommendation algorithm for learning resources, Multimed. Syst., .
Y. Koren, Factorization meets the neighborhood: A multifaceted collaborative filtering model, in Proc. 14th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, Las Vegas, NV, USA, 2008, pp. 426-434.
B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, Item-based collaborative filtering recommendation algorithms, in Proc. 10th Int. Conf. World Wide Web, Hong Kong, China, 2001, pp. 285-295.
A. Felfernig, Koba4MS: Selling complex products and services using knowledge-based recommender technologies, in Proc. 7th IEEE Int. Conf. E-Commerce Technology, Munich, Germany, 2005, pp. 92-100.
A. Felfernig and K. Shchekotykhin, Debugging user interface descriptions of knowledge-based recommender applications in Proc. 11st Int. Conf. Intelligent User Interfaces, Sydney, Australia, 2006, pp. 234-241.
J. Wang, A. P. De Vries, and M. J. T. Reinders, Unifying user-based and item-based collaborative filtering approaches by similarity fusion, in Proc. 29th Annual Int. ACM SIGIR Conf. Research and Development in Information Retrieval, Seattle, WA, USA, 2006, pp. 501-508.
B. L. Wang, J. H. Huang, L. B. Ou, and R. Wang, A collaborative filtering algorithm fusing user-based, item-based and social networks, in Proc. 2015 IEEE Int. Conf. Big Data, Santa Clara, CA, USA, 2015, pp. 2337-2343.
H. Koohi and K. Kiani, User based collaborative filtering using fuzzy c-means, Measurement, vol. 91, pp. 134-139, 2016.
X. Y. Liu, C. Aggarwal, Y. F. Li, X. N. Kong, X. Y. Sun, and S. Sathe, Kernelized matrix factorization for collaborative filtering, in Proc. 2016 Siam Int. Conf. Data Mining, Miami, FL, USA, 2016, pp. 378-386.
T. Hofmann, Latent semantic models for collaborative filtering, ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 89-115, 2004.
R. Salakhutdinov, A. Mnih, and G. Hinton, Restricted Boltzmann machines for collaborative filtering, in Proc. 24th Int. Conf. Machine Learning, Corvalis, OR, USA, 2007, pp. 791-798.
H. L. Xu, X. Wu, X. D. Li, and B. P. Yan, Comparison Study of internet recommendation system, (in Chinese), J. Softw., vol. 20, no. 2, pp. 350-362, 2009.
M. K. Najafabadi, M. N. Mahrin, S. Chuprat, and H. M. Sarkan, Improving the accuracy of collaborative filtering recommendations using clustering and association rules mining on implicit data, Comput. Hum. Behav., vol. 67, pp. 113-128, 2017.
N. Gao and M. Yang, An improved unifying tags and ratings collaborative filtering for recommendation system, (in Chinese), J. Nanjing Nor. Univ. (Nat. Sci. Ed.), vol. 38, no. 1, pp. 98-103, 2015.
H. Koohi and K. Kiani, A new method to find neighbor users that improves the performance of collaborative filtering, Expert Syst. Appl., vol. 83, no. C, pp. 30-39, 2017.
D. Goldberg, D. Nichols, B. M. Oki, and D. Terry, Using collaborative filtering to weave an information tapestry, Commun. ACM, vol. 35, no. 12, pp. 61-70, 1992.
Z. D. Zhao and M. S. Shang, User-based collaborative-filtering recommendation algorithms on hadoop, in Proc. 3rd Int. Conf. Knowledge Discovery and Data Mining, Phuket, Thailand, 2010, 478-481.
H. Ji, J. F. Li, C. R. Ren, and M. He, Hybrid collaborative filtering model for improved recommendation, in Proc. 2013 IEEE Int. Conf. Service Operations and Logistics, and Informatics, Dongguan, China, 2013.
S. Y. Wei, N. Ye, S. Zhang, X. Huang, and J. Zhu, Item-based collaborative filtering recommendation algorithm combining item category with interestingness measure, in Proc. 2012 Int. Conf. Computer Science and Service System, Nanjing, China, 2012, pp. 2038-2041.
G. Karypis, Evaluation of item-based top-N recommendation algorithms, in Proc. 10th Int. Conf. Information and Knowledge Management, Atlanta, GA, USA, 2001, pp. 247-254.
P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, GroupLens: An open architecture for collaborative filtering of Netnews, in Proc. 1994 ACM Conf. Computer Supported Cooperative Work, Chapel Hill, NC, USA, 1994, pp. 175-186.