Addressing the user cold start with cross-domain collaborative filtering: exploiting item metadata in matrix factorization-Reference-Cited by-同舟云学术

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Addressing the user cold start with cross-domain collaborative filtering: exploiting item metadata in matrix factorization

Published:2019-01-01 Issue:2 Volume:29 Page:443-486
ISSN:0924-1868
Container-title:User Modeling and User-Adapted Interaction
language:en
Short-container-title:User Model User-Adap Inter

Author:

Fernández-Tobías Ignacio,Cantador Iván,Tomeo Paolo,Anelli Vito Walter,Di Noia Tommaso

Funder

Ministerio de Economía y Competitividad

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Education

Link

http://link.springer.com/content/pdf/10.1007/s11257-018-9217-6.pdf

Reference76 articles.

1. Abel, F., Araújo, S., Gao, Q., Houben, G.J.: Analyzing cross-system user modeling on the social web. In: Proceedings of the 11th International Conference on Web Engineering (ICWE’11), pp. 28–43 (2011)

2. Abel, F., Herder, E., Houben, G.J., Henze, N., Krause, D.: Cross-system user modeling and personalization on the social web. User Model. User Adap. Interact. 23(2–3), 169–209 (2013)

3. Bell, R.M., Koren, Y.: Lessons from the Netflix prize challenge. SIGKDD Explor. 9(2), 75–79 (2007a)

4. Bell, R.M., Koren, Y.: Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In: Proceedings of the 7th IEEE International Conference on Data Mining (ICDM’07), pp. 43–52 (2007b)

5. Bellogín, A., Fernández-Tobías, I., Cantador, I., Tomeo, P.: Neighbor selection for cold users in collaborative filtering with positive-only feedback. In: Proceedings of the 18th Conference of the Spanish Association for Artificial Intelligence (CAEPIA’18), pp. 3–12 (2018)

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