Comparison of the Non-personalized Active Learning Strategies Used in Recommender Systems
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Springer International Publishing
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http://link.springer.com/content/pdf/10.1007/978-3-030-11395-7_34
Reference33 articles.
1. Lops, P., de Gemmis, M., Semeraro, G.: Content-based recommender systems: state of the art and trends. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 73–105. Springer, Boston (2011). https://doi.org/10.1007/978-0-387-85820-3_3
2. de Gemmis, M., Lops, P., Musto, C., Narducci, F., Semeraro, G.: Semantics-aware content-based recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 119–159. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_4
3. Wang, Y., Chan, S.C.-F., Ngai, G.: Applicability of demographic recommender system to tourist attractions: a case study on trip advisor. In: Proceedings of the 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, WI-IAT 2012, vol. 03, pp. 97–101. IEEE Computer Society, Washington, DC (2012)
4. Beliakov, G., Calvo, T., James, S.: Aggregation functions for recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 777–808. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_23
5. Burke, R.: Knowledge-based recommender systems (2000)
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