Survey

Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions. [arXiv]

Tutorial

WSDM 2022, Graph Neural Networks for Recommender System [Website][Slides]

IJCAI 2021, Towards Automated Recommender System [Website][Slides]

KDD 2020, Advances in Recommender System [Website][Slides]

Publications [Google Scholar]

(*corresponding author)

In the year of 2022:

• Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks. Y. Li, Chen Gao*, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li. (CIKM'22)

• DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias. Y. Zheng, Chen Gao*, J. Ding, L. Yi, D. Jin, Y. Li, and M. Wang. (ACM MM'22, oral)

• Automatically Discovering User Consumption Intents in Meituan. Y. Li, Chen Gao*, X. Du, H. Wei, H. Luo, D. Jin, and Y. Li. (KDD'22)

• Modeling the Effect of Persuasion Factor on User Decision for Recommendation. C. Liu, Chen Gao*, Y. Yuan, C. Bai, L. Luo, X. Du, H. Luo, D. Jin, and Y. Li. (KDD'22)

• Disentangled Modeling of Social Homophily and Influence for Social Recommendation. N. Li, Chen Gao*, D. Jin and Q. Liao. (TKDE'22)

• Dual Contrastive Network for Sequential Recommendation. G. Lin, Chen Gao*, Y. Li, Y. Zheng, Z. Li, D. Jin and Y. Li. (SIGIR'22, short)

• Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation. Y. Li, Chen Gao*, H. Luo, D. Jin and Y. Li (SIGIR'22, short)

• DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction. Y. Li, Chen Gao*, Q. Yao, T. Li, D. Jin and Y. Li. (ICDE'22)

• Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks. Z. Zhu, Chen Gao, X. Chen, N. Li, D. Jin and Y. Li. (ICDE'22)

• Disentangling Long and Short-Term Interests for Recommendation. Y. Zheng, Chen Gao*, J. Chang, Y. Niu, Y. Song, D. Jin and Y. Li. (TheWebConf/WWW'22)

• Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design. Z. Chen, J. Piao, X. Lan, H. Cao, Chen Gao, Z. Lu and Y. Li. (CSCW'22)

In the year of 2021:

• Progressive Feature Interaction Search for Deep Sparse Network. Chen Gao, Y. Li, Q. Yao, D. Jin and Y. Li. (NeurIPS'21)

• Bundle Recommendation and Generation with Graph Neural Networks . J. Chang, Chen Gao*, X. He, D. Jin and Y. Li. (TKDE'21)

• Cross-platform Item Recommendation for Online Social E-Commerce. Chen Gao, TH. Lin, N. Li, D. Jin and Y. Li. (TKDE'21)

• Incorporating Price into Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, X. He, D. Jin and Y. Li. (TKDE'21)

• Bringing Friends into the Loop of Recommender Systems: An Exploratory Study. J. Piao, G. Zhang, F. Xu, Z. Chen, Y. Zheng, Chen Gao and Y. Li. (CSCW'21)

• Efficient Data-specific Model Search for Collaborative Filtering. Chen Gao, Q. Yao, D. Jin and Y. Li. (KDD'21)

• User Consumption Intention Prediction in Meituan. Y. Ping, Chen Gao, T. Liu, X. Du, H. Luo, D. Jin and Y. Li. (KDD'21)

• Sequential Recommendation with Graph Neural Networks. J. Chang, Chen Gao, Y. Zheng, Y. Hui, Y. Niu, Y. Song, D. Jin and Y. Li. (SIGIR'21)

• Cross-domain Recommendation with Bridge-Item Embeddings. Chen Gao, Y. Li, F. Feng, X. Chen, K. Zhao, X. He and D. Jin. (TKDD'21)

• Learnable Embedding Sizes for Recommender Systems. S. Liu, Chen Gao*, Y. Chen, D. Jin and Y. Li. (ICLR'21)

• Group-Buying Recommendation for Social E-Commerce. J. Zhang, Chen Gao*, D. Jin and Y. Li. (ICDE'21)

• Disentangling User Interest and Conformity for Recommendation with Causal Embedding. Y. Zheng, Chen Gao, X. Li, X. He, D. Jin and Y. Li. (TheWebConf/WWW'21)

• DGCN: Diversified Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, L. Chen, D. Jin and Y. Li. (TheWebConf/WWW'21)

In the year of 2020:

• Differentially Private Local Collaborative Filtering. Chen Gao, C. Huang, D. Lin, D. Jin and Y. Li. (SIGIR'20)

• Multi-behavior Recommendation with Graph Convolutional Networks. B. Jin, Chen Gao, X. He, D. Jin and Y. Li. (SIGIR'20)

• Item Recommendation for Word-of-Mouth Scenario in Social E-Commerce. Chen Gao, C. Huang, D. Yu, TH. Lin, H. Fu, D. Jin and Y. Li. (TKDE'20)

• Social Recommendation with Characteristic Regularization. Chen Gao, N. Li, TH. Lin, D. Lin, J. Zhang, Y. Li and D. Jin. (TKDE'20)

• Bundle Recommendation with Graph Convolutional Networks. J. Chang, Chen Gao, X. He, D. Jin and Y. Li.(SIGIR'20, Best Short Paper Honorable Mention Award)

• Price-aware Recommendation with Graph Convolutional Networks. Y. Zheng, Chen Gao, X. He, Y. Li and D. Jin. (ICDE'20)

• Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs . H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (TNSM'20)

In the year of 2019:

• Learning to Recommend with Multiple Cascading Behaviors. Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua and D. Jin. (TKDE'19)

• Cross-domain Recommendation without Sharing User-relevant Data. Chen Gao, X. Chen, F. Feng, K. Zhao, X. He, Y. Li and D. Jin. (TheWebConf/WWW'19)

• Privacy-preserving Cross-domain Location Recommendation. Chen Gao, C. Huang, Y. Yu, H. Wang, Y. Li and D. Jin. (IMWUT/UbiComp'19)

• Neural Multi-Task Recommendation from Multi-Behavior Data. Chen Gao, X. He, D. Gan, X. Chen, F. Feng, Y. Li, TS. Chua and D. Jin. (ICDE'19, short)

• CROSS: Cross-platform Recommendation for Online Shopping in Social Media. TH. Lin, Chen Gao and Y. Li. (SIGIR'19)

• λOpt: Learn to Regularize Recommender Models in Finer Levels. Y. Chen, B. Chen, X. He, Chen Gao, Y. Li, JG. Lou and Y. Wang. (KDD'19)

• DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation. H. Yan, X.. Chen, Chen Gao, Y. Li and D. Jin. (IJCAI'19)

• Anonymization and De-anonymization of Mobility Trajectories: Dissecting the Gaps between Theory and Practice. H. Wang, Y. Li, Chen Gao, G. Wang, X. Tao and D. Jin. (TMC'19)

Before 2019:

• Recommender Systems with Characteristic Social Regularization. TH. Lin, Chen Gao and Y. Li. (CIKM'18, short)

• De-anonymization of Mobility Trajectories: Dissecting the Gaps between Theory and Practice. H. Wang, Chen Gao, Y. Li, G. Wang, D. Jin and J. Sun. (NDSS'18)

• From Fingerprint to Footprint: Revealing Physical World Privacy Leakage by Cyberspace Cookie Logs. H. Wang, Chen Gao, Y. Li, ZL. Zhang and D. Jin. (CIKM'17)