Tutorial: Educational Recommender Systems
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36336-8_7
Reference32 articles.
1. Abdollahpouri, H., et al.: Multistakeholder recommendation: survey and research directions. User Model. User-Adap. Inter. 30(1), 127–158 (2020). https://doi.org/10.1007/s11257-019-09256-1
2. Adomavicius, G., Manouselis, N., Kwon, Y.O.: Multi-criteria recommender systems. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 769–803. Springer, Boston, MA (2011). https://doi.org/10.1007/978-0-387-85820-3_24
3. Burke, R., Zheng, Y., Riley, S.: Experience discovery: hybrid recommendation of student activities using social network data. In: Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, pp. 49–52 (2011)
4. Cantador, I., Fernández-Tobías, I., Berkovsky, S., Cremonesi, P.: Cross-domain recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 919–959. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_27
5. Drachsler, H., Verbert, K., Santos, O.C., Manouselis, N.: Panorama of recommender systems to support learning. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 421–451. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_12
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