Author:
Peng Yingtao,Zhao Zhendong,Maoliniyazi Aishan,Meng Xiaofeng
Publisher
Springer Nature Switzerland
Reference38 articles.
1. Bian, S., Zhao, W.X., Zhou, K., et al.: Contrastive curriculum learning for sequential user behavior modeling via data augmentation. In: The 30th ACM International Conference on Information and Knowledge Management (CIKM) (2021)
2. Cao, Y., Wang, X., He, X., et al.: Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences. In: The World Wide Web Conference (WWW), pp. 151–161 (2019)
3. Chen, C., Zhang, M., Ma, W., et al.: Jointly non-sampling learning for knowledge graph enhanced recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 189–198 (2020)
4. Chen, J., Zhang, H., He, X., et al.: Attentive collaborative filtering: multimedia recommendation with item-and component-level attention. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (2017)
5. Chen, T., Kornblith, S., Norouzi, M., et al.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning (ICML), pp. 1597–1607 (2020)