Hybrid Recommendation of Movies Based on Deep Content Features-Reference-Cited by-同舟云学术

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Hybrid Recommendation of Movies Based on Deep Content Features

Published:2022 Issue: Volume: Page:32-45
ISSN:0302-9743
Container-title:Service-Oriented Computing – ICSOC 2021 Workshops
language:
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Author:

Kvifte Tord,Elahi Mehdi,Trattner Christoph

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-14135-5_3

Reference50 articles.

1. Aggarwal, C.C., et al.: Recommender Systems, vol. 1. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29659-3

2. Canini, L., Benini, S., Leonardi, R.: Affective recommendation of movies based on selected connotative features. IEEE Trans. Circuits Syst. Video Technol. 23(4), 636–647 (2013)

3. Cantador, I., Bellogín, A., Vallet, D.: Content-based recommendation in social tagging systems. In: Proceedings of the Fourth ACM Conference on Recommender Systems, pp. 237–240. ACM (2010)

4. Cantador, I., Konstas, I., Jose, J.M.: Categorising social tags to improve folksonomy-based recommendations. Web Semant. 9(1), 1–15 (2011)

5. 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

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