Collaborative Multi-Auxiliary Information Variational Autoencoder for Recommender Systems-Reference-Cited by-同舟云学术

Collaborative Multi-Auxiliary Information Variational Autoencoder for Recommender Systems

Published:2019 Issue: Volume: Page:
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Container-title:Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
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Author:

Bai Jinxin¹,Ban Zhijie¹

Affiliation:

1. College of Computer Science, Inner Mongolian University, Hohhot, Inner Mongolia Autonomous Region, China

Publisher

ACM Press

Reference22 articles.

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3. Isinkaye, F. O., Folajimi, Y. O., & Ojokoh, B. A. 2015. Recommendation systems: Principles, methods and evaluation. Egyptian Informatics Journal, 16(3), 261--273.

4. Lang, K. 1995. Newsweeder: Learning to filter netnews. In Machine Learning Proceedings 1995, pp. 331--339.

5. Mooney, R. J., & Roy, L. 2000. Content-based book recommending using learning for text categorization. In Proceedings of the fifth ACM conference on Digital libraries(pp. 195--204). ACM.

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