Improved negative sampling method in collaborative filtering recommendation based on Generative adversarial network
Author:
Funder
Chinese National Funding of Social Sciences
Publisher
Elsevier BV
Reference34 articles.
1. Bharadhwaj, H., Park, H., Lim, B. Y., 2018. RecGAN: recurrent generative adversarial networks for recommendation systems. In Proceedings of the 12th ACM Conference on Recommender Systems. pp. 372-376.
2. Chae, D. K., Kang, J.S., Kim,S.W., Lee, J.T., 2018. CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). Association for Computing Machinery, New York, NY, USA, 137–146.
3. Chae, D. K., Kim, S. W., 2018. Adversarial training of deep autoencoders towards recommendation tasks. In 2018 International Conference on Network Infrastructure and Digital Content (IC-NIDC). IEEE. pp. 91-95.
4. Chae, D. K., Kim, J., Chau, D. H., Kim, S. W., 2020. Ar-cf: Augmenting virtual users and items in collaborative filtering for addressing cold-start problems. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. pp. 1251-1260.
5. Collaborative adversarial autoencoders: An effective collaborative filtering model under the GAN framework;Chae;IEEE Access,2019
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