1. Ziegler, C.N., McNee, S.M., Konstan, J.A., Lausen, G.: Improving recommendation lists through topic diversification. In: Proceedings of the 14th International Conference on World Wide Web, New York, NY, USA, vol. 2131, no. 34, pp. 222–234 (2005)
2. Gokulakrishnan, B., Priyanthan, P., Raghavan, T., Prasath, N., Perera, A.: Opinion mining and sentiment analysis on a twitter data stream. In: The International Conference on Advances in ICT for Emerging Regions, vol. 46, no. 12, pp. 182–188 (2012)
3. Singh, Y., Bhatia, P., Sangwan, O.: A review of studies on machine learning techniques. Int. J. Comput. Sci. Secur. 1(1), 70–84 (2007)
4. Tejeda, A.: A quality-based recommender system to disseminate information in a university digital library. Inf. Sci. 261(32), 52–69 (2014)
5. Fan, Y., Dong, L., Sun, X., Wang, D., Qin, W., Aizeng, C.: Research on auto-generating test-paper model based on spatial-temporal clustering analysis. In: Huang, D.S., Jo, K.H., Zhang, X.L. (eds.) Intelligent Computing Theories and Application, ICIC, Lecture Notes in Computer Science, vol. 10955, no. 2342, pp. 238–255. Springer, Cham (2018)