微信AI:基于“朋友在看”的好友增强型推荐

   日期:2024-12-25    作者:n9vii 移动:http://oml01z.riyuangf.com/mobile/quote/11709.html

[1] Chen, Chong, et al. "Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34. No. 01. 2020.

微信AI:基于“朋友在看”的好友增强型推荐


[2] Dong, Yuxiao, Nitesh V. Chawla, and Ananthram Swami. "metapath2vec: Scalable representation learning for heterogeneous networks." Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining. 2017.


[3] Fan, Wenqi, et al. "Graph neural networks for social recommendation." The World Wide Web Conference. 2019.


[4] Grover, Aditya, and Jure Leskovec. "node2vec: Scalable feature learning for networks." Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining. 2016.


[5] Kipf, Thomas N., and Max Welling. "Semi-supervised classification with graph convolutional networks." arXiv preprint arXiv:1609.02907 (2016).


[6] Perozzi, Bryan, Rami Al-Rfou, and Steven Skiena. "Deepwalk: Online learning of social representations." Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. 2014.


[7] Shi, Chuan, et al. "Heterogeneous information network embedding for recommendation." IEEE Transactions on Knowledge and Data Engineering 31.2 (2018): 357-370.


[8] Veličković, Petar, et al. "Graph attention networks." arXiv preprint arXiv:1710.10903 (2017).


[9] Wang, Xiao, et al. "Heterogeneous graph attention network." The World Wide Web Conference. 2019


[10] Wu, Le, et al. "A neural influence diffusion model for social recommendation." Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval. 2019.



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