Multi-neighbor social recommendation with attentional graph convolutional network (original) (raw)
Bordes A, Usunier N, Duran AG (2013) Translating embeddings for modeling multirelational data. In: Proceedings of the 26th International Conference on Neural Information Processing Systems, vol 2, pp 2787–2795
Cheng HT, Koc L, Harmsen J (2016) Wide and deep learning for recommender systems. In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems
Chen B, Guo W, Tang RM (2020) Tgcn: tag graph convolutional network for tag-aware recommendation. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management, pp 155–164
Defferrard M, Bresson X, Vandergheyns P (2016) Convolutional neural networks on graphs with fast localized spectral filtering. Adv Neural Inf Process Syst 29:3844–3852 Google Scholar
Fan WQ, Ma Y, Li Q (2019) Graph neural networks for social recommendation. In: Proceedings of the 28th International Conference on World Wide Web, pp 417–426
Goldberg D, Nichols D, Oki BM (1992) Using collaborative filtering to weave an information tapestry. Commun ACM 35:61–70 Article Google Scholar
Gong JB, Wang S, Wang JL (2020) Attentional graph convolutional networks for knowledge concept recommendation in moocs in a heterogeneous view. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 79–88
Guo HF, Tang RM, Ye YM (2017) Deepfm: a factorization-machine based neural network for ctr prediction. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp 1725–1731
He XN, Chua TS (2017) Neural factorization machines for sparse predictive analytics. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 355–364
He XN, Liao LZ, Zhang HW (2017) Neural collaborative filtering. In: Proceedings of the 26th International Conference on World Wide Web, pp 173–182
He XR, Pan JF, Jin O (2014) Practical lessons from predicting clicks on ads at Facebook. In: Proceedings of the 8th International Workshop Advertising
Jamali M, Ester MA (2012) matrix factorization technique with trust propagation for recommendation in social networks. In: Proceedings of the 4th ACM Conference on Recommender Systems, pp 135–142
Jin BW, Gao C, He XN (2020) Multi-behavior recommendation with graph convolutional networks. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 659–668
Juan YC, Zhuang Y, Chin WS (2016) Field-aware factorization machines for ctr prediction. In: Proceedings of the 10th ACM Conference on Recommender Systems, pp 43–50
Koren Y (2008) Factorization meets the neighborhood: a multifaceted collaborative filtering model. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 426–434
Koren Y, Bell R, Volinsky C (2009) Matrix factorization techniques for recommender systems. IEEE Open J Comput Soc 18:42–49 Google Scholar
Li WT, Gao M, Rong WG (2017) Social recommendation using euclidean embedding. International Joint Conference on Neural Networks IEEE
Lin YK, Liu ZY, Sun MS (2015) Learning entity and relation embeddings for knowledge graph completion. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence, pp 2181–2187
Liu BH, Zhao PP, Zhuang FZ (2021) Knowledge-aware hypergraph neural network for recommender systems. International Conference on Database Systems for Advanced Applications, pp 132–147
Ma H, King I, Lyu MR (2009) Learning to recommend with social trust ensemble. In: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 203–210
Ma H, Yang HX, Lyu MR (2008) Sorec: social recommendation using probabilistic matrix factorization. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp 931–940
Ma H, Zhou DY, Liu C (2011) Recommender systems with social regularization. In: Proceedings of the 4th ACM International Conference on Web Search and Data Mining, pp 287–296
Rendle S (2010) Factorization machines. In: Proceedings of the 2010 IEEE International Conference on Data Mining, pp 995–1000
Salakhutdinov R, Mnih A (2007) Probabilistic matrix factorization. Adv Neural Inf Process Syst 20:1–8 Google Scholar
Sedhain S, Menon AK, Sanner S (2015) Autorec: autoencoders meet collaborative filtering. In: Proceedings of the 24th International Conference on World Wide Web, pp 111–112
Shan Y, Hoens TR, Jiao J (2016) Deep crossing: web-scale modeling without manually crafted combinatorial features. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 255–262
Sun JN, Zhang YX, Guo W (2020) Neighbor interaction aware graph convolution networks for recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 1289–1298
Sun R, Cao XZ, Zhao Y (2020) Multi-modal knowledge graphs for recommender systems. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management, pp 1405–1414
Tang JL, Hu X, Gao HJ (2013) Exploiting local and global social context for recommendation. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence, pp 2712–2718
Vozalis MG, Margaritis KG (2007) Using SVD and demographic data for the enhancement of generalized collaborative filtering. Int J Inf Sci Technol 177:3017–3037 Google Scholar
Wang X, He XN, Cao YX (2019) Kgat: knowledge graph attention network for recommendation. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 950–958
Wu L, Li JW, Sun P (2020) Diffnet++: a neural influence and interest diffusion network for social recommendation. IEEE Trans Knowl Data Eng 34:3048414 Google Scholar
Wu SW, Sun F, Zhang WT (2022) Graph neural networks in recommender systems: a survey. ACM Comput Surv 37(4):1–34 Google Scholar
Wu L, Sun P, Fu YA (2019) neural influence diffusion model for social recommendation. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 235–244
Xu K, Li CT, Tian YL (2018) Representation learning on graphs with jumping knowledge networks. In: Proceedings of the 35th International Conference on Machine Learning, vol 80, pp 5449–5458
Yang LW, Liu ZW, Dou YT (2021) Consisrec: enhancing gnn for social recommendation via consistent neighbor aggregation. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 2141–2145
Yang B, Lei Y, Liu JM (2016) Social collaborative filtering by trust. IEEE Trans Pattern Anal Mach Intell 39(8):1–14 Google Scholar
Yin RP, Li K, Zhang GQ (2019) A deeper graph neural network for recommender systems. Knowl-Based Syst 185(1):66 Google Scholar
Yu JL, Yin HZ, Li JD (2020) Enhancing social recommendation with adversarial graph convolutional networks. IEEE Transactions on Knowledge and Data Engineering, pp 1–13
Zhang WN, Du TM, Wang J (2016) Deep learning over multi-field categorical data. European Conference on Information Retrieval, pp 45–57
Zhang SA, Yao LN, Sun AX (2020) Deep learning based recommender system: a survey and new perspectives. ACM Comput Surv 52(1):1–38 Google Scholar
Zhang J, Gao C, Jin DP (2021) Group-buying recommendation for social e-commerce. IEEE 37th International Conference on Data Engineering, pp 1536–1547