Jiawei Chen

According to our database, Jiawei Chen authored at least 93 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Breaking the Top-<i>K</i> Barrier: Advancing Top-<i>K</i> Ranking Metrics Optimization in Recommender Systems.

Weiqin Yang, Jiawei Chen, Shengjia Zhang, Peng Wu, Yuegang Sun, Yan Feng, Chun Chen, Can Wang

CoRR, August, 2025

Addressing Information Asymmetry: Deep Temporal Causality Discovery for Mixed Time Series.

Jiawei Chen, Chunhui Zhao

IEEE Trans. Pattern Anal. Mach. Intell., July, 2025

OpenGT: A Comprehensive Benchmark For Graph Transformers.

Jiachen Tang, Zhonghao Wang, Sirui Chen, Sheng Zhou, Jiawei Chen, Jiajun Bu

CoRR, June, 2025

OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation.

Shengjia Zhang, Junjie Wu, Jiawei Chen, Changwang Zhang, Xingyu Lou, Wangchunshu Zhou, Sheng Zhou, Can Wang, Jun Wang

CoRR, June, 2025

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions.

Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester

ACM Comput. Surv., March, 2025

Recent Advances on Generalizable Diffusion-generated Image Detection.

Qijie Xu, Defang Chen, Jiawei Chen, Siwei Lyu, Can Wang

CoRR, February, 2025

Future-Conditioned Recommendations with Multi-Objective Controllable Decision Transformer.

Chongming Gao, Kexin Huang, Ziang Fei, Jiaju Chen, Jiawei Chen, Jianshan Sun, Shuchang Liu, Qingpeng Cai, Peng Jiang

CoRR, January, 2025

Conditional Image Synthesis with Diffusion Models: A Survey.

Zheyuan Zhan, Defang Chen, Jian-Ping Mei, Zhenghe Zhao, Jiawei Chen, Chun Chen, Siwei Lyu, Can Wang

Trans. Mach. Learn. Res., 2025

Frequency Self-Adaptation Graph Neural Network for Unsupervised Graph Anomaly Detection.

Ming Gu, Gaoming Yang, Zhuonan Zheng, Meihan Liu, Haishuai Wang, Jiawei Chen, Sheng Zhou, Jiajun Bu

Neural Networks, 2025

Uncertainty-Aware Graph Structure Learning.

Shen Han, Zhiyao Zhou, Jiawei Chen, Zhezheng Hao, Sheng Zhou, Gang Wang, Yan Feng, Chun Chen, Can Wang

Proceedings of the ACM on Web Conference 2025, 2025

Rankformer: A Graph Transformer for Recommendation based on Ranking Objective.

Sirui Chen, Shen Han, Jiawei Chen, Binbin Hu, Sheng Zhou, Gang Wang, Yan Feng, Chun Chen, Can Wang

Proceedings of the ACM on Web Conference 2025, 2025

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding.

Zhe Wang, Sheng Zhou, Jiawei Chen, Zhen Zhang, Binbin Hu, Yan Feng, Chun Chen, Can Wang

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective.

Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data.

Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender.

Bohao Wang, Feng Liu, Jiawei Chen, Xingyu Lou, Changwang Zhang, Jun Wang, Yuegang Sun, Yan Feng, Chun Chen, Can Wang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization.

Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution.

Shengjia Zhang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

ReCRec: Reasoning the Causes of Implicit Feedback for Debiased Recommendation.

Siyi Lin, Sheng Zhou, Jiawei Chen, Yan Feng, Qihao Shi, Chun Chen, Ying Li, Can Wang

ACM Trans. Inf. Syst., November, 2024

How graph convolutions amplify popularity bias for recommendation?

Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

Frontiers Comput. Sci., October, 2024

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.

Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu

ACM Trans. Inf. Syst., July, 2024

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System.

Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang

ACM Trans. Inf. Syst., January, 2024

Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling.

Jiawei Chen, Pengyu Song, Chunhui Zhao

Pattern Recognit., January, 2024

Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation.

Weizhi Nie, Xin Wen, Jing Liu, Jiawei Chen, Jiancan Wu, Guoqing Jin, Jing Lu, An-An Liu

IEEE Trans. Multim., 2024

Position-aware Graph Transformer for Recommendation.

Jiajia Chen, Jiancan Wu, Jiawei Chen, Chongming Gao, Yong Li, Xiang Wang

CoRR, 2024

Universal Inceptive GNNs by Eliminating the Smoothness-generalization Dilemma.

Ming Gu, Zhuonan Zheng, Sheng Zhou, Meihan Liu, Jiawei Chen, Tanyu Qiao, Liangcheng Li, Jiajun Bu

CoRR, 2024

Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power.

Zhe Wang, Tianjian Zhao, Zhen Zhang, Jiawei Chen, Sheng Zhou, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective.

Binbin Hu, Weifan Wang, Hanshu Wang, Ziqi Liu, Bin Shen, Yong He, Jiawei Chen

CoRR, 2024

LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation.

Bohao Wang, Feng Liu, Jiawei Chen, Yudi Wu, Xingyu Lou, Jun Wang, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

Motif-driven Subgraph Structure Learning for Graph Classification.

Zhiyao Zhou, Sheng Zhou, Bochao Mao, Jiawei Chen, Qingyun Sun, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

Better Late Than Never: Formulating and Benchmarking Recommendation Editing.

Chengyu Lai, Sheng Zhou, Zhimeng Jiang, Qiaoyu Tan, Yuanchen Bei, Jiawei Chen, Ningyu Zhang, Jiajun Bu

CoRR, 2024

Towards a Unified Framework of Clustering-based Anomaly Detection.

Zeyu Fang, Ming Gu, Sheng Zhou, Jiawei Chen, Qiaoyu Tan, Haishuai Wang, Jiajun Bu

CoRR, 2024

Revisiting the Message Passing in Heterophilous Graph Neural Networks.

Zhuonan Zheng, Yuanchen Bei, Sheng Zhou, Yao Ma, Ming Gu, Hongjia Xu, Chengyu Lai, Jiawei Chen, Jiajun Bu

CoRR, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model.

Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

CoRR, 2024

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective.

Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Can Wang

CoRR, 2024

EasyRL4Rec: A User-Friendly Code Library for Reinforcement Learning Based Recommender Systems.

Yuanqing Yu, Chongming Gao, Jiawei Chen, Heng Tang, Yuefeng Sun, Qian Chen, Weizhi Ma, Min Zhang

CoRR, 2024

Knowledge Translation: A New Pathway for Model Compression.

Wujie Sun, Defang Chen, Jiawei Chen, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

Distributionally Robust Graph-based Recommendation System.

Bohao Wang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yang Gao, Yan Feng, Chun Chen, Can Wang

Proceedings of the ACM on Web Conference 2024, 2024

EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems.

Yuanqing Yu, Chongming Gao, Jiawei Chen, Heng Tang, Yuefeng Sun, Qian Chen, Weizhi Ma, Min Zhang

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

SIGformer: Sign-aware Graph Transformer for Recommendation.

Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool.

Changxin Tian, Binbin Hu, Chunjing Gan, Haoyu Chen, Zhuo Zhang, Li Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Jiawei Chen

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models.

Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment.

Jiawei Chen, Chunhui Zhao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation.

Weiqin Yang, Jiawei Chen, Xin Xin, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

BSL: Understanding and Improving Softmax Loss for Recommendation.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding.

Yichen Liu, Jiawei Chen, Defang Chen, Zhehui Zhou, Yan Feng, Can Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective.

Binbin Hu, Weifan Wang, Shuhan Wang, Ziqi Liu, Bin Shen, Yong He, Jiawei Chen

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation.

Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu

IEEE Trans. Knowl. Data Eng., October, 2023

Time-aware Path Reasoning on Knowledge Graph for Recommendation.

Yuyue Zhao, Xiang Wang, Jiawei Chen, Yashen Wang, Wei Tang, Xiangnan He, Haiyong Xie

ACM Trans. Inf. Syst., April, 2023

Information Retrieval meets Large Language Models: A strategic report from Chinese IR community.

Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu

AI Open, January, 2023

Bias and Debias in Recommender System: A Survey and Future Directions.

Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, Xiangnan He

ACM Trans. Inf. Syst., 2023

SamWalker++: Recommendation With Informative Sampling Strategy.

Can Wang, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen

IEEE Trans. Knowl. Data Eng., 2023

Spatiotemporal Multiscale Correlation Embedding With Process Variable Reorder for Industrial Soft Sensing.

Jiawei Chen, Pengyu Song, Chunhui Zhao, Jinliang Ding

IEEE Trans. Instrum. Meas., 2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He

CoRR, 2023

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion.

Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He

CoRR, 2023

On the Theories Behind Hard Negative Sampling for Recommendation.

Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Unbiased Knowledge Distillation for Recommendation.

Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

A Generic Learning Framework for Sequential Recommendation with Distribution Shifts.

Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation.

Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang, Xiangnan He

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning.

Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Contrastive Learning via Distributionally Robust Optimization.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discriminative-Invariant Representation Learning for Unbiased Recommendation.

Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, Xiangnan He

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

CDR: Conservative Doubly Robust Learning for Debiased Recommendation.

Zijie Song, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Homophily-enhanced Structure Learning for Graph Clustering.

Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Robust Sequence Networked Submodular Maximization.

Qihao Shi, Bingyang Fu, Can Wang, Jiawei Chen, Sheng Zhou, Yan Feng, Chun Chen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

KuaiRec: A Fully-observed Dataset for Recommender Systems.

Chongming Gao, Shijun Li, Wenqiang Lei, Biao Li, Peng Jiang, Jiawei Chen, Xiangnan He, Jiaxin Mao, Tat-Seng Chua

CoRR, 2022

Neighboring Backdoor Attacks on Graph Convolutional Network.

Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng

CoRR, 2022

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.

Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, Xiangnan He

CoRR, 2022

IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search.

Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos.

Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, Xiangnan He

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems.

Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, Tat-Seng Chua

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation.

Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, Xiangnan He

ACM Trans. Inf. Syst., 2021

Profit maximization for competitive social advertising.

Qihao Shi, Can Wang, Deshi Ye, Jiawei Chen, Sheng Zhou, Yan Feng, Chun Chen, Yanhao Huang

Theor. Comput. Sci., 2021

CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation.

Xu Xie, Zhaoyang Liu, Shiwen Wu, Fei Sun, Cihang Liu, Jiawei Chen, Jinyang Gao, Bin Cui, Bolin Ding

CoRR, 2021

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation.

Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui

Proceedings of the WWW '21: The Web Conference 2021, 2021

AutoDebias: Learning to Debias for Recommendation.

Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021.

Jiawei Chen, Xiang Wang, Fuli Feng, Xiangnan He

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Distilling Holistic Knowledge with Graph Neural Networks.

Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

CausCF: Causal Collaborative Filtering for Recommendation Effect Estimation.

Xu Xie, Zhaoyang Liu, Shiwen Wu, Fei Sun, Cihang Liu, Jiawei Chen, Jinyang Gao, Bin Cui, Bolin Ding

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network.

Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Chufeng Shi, Ziwei Wu, Jinfeng Yi, Xiangnan He

CoRR, 2020

Sparse Causal Residual Neural Network for Linear and Nonlinear Concurrent Causal Inference and Root Cause Diagnosis.

Jiawei Chen, Chunhui Zhao, Youxian Sun

Proceedings of the 16th International Conference on Control, 2020

DGE: Deep Generative Network Embedding Based on Commonality and Individuality.

Sheng Zhou, Xin Wang, Jiajun Bu, Martin Ester, Pinggang Yu, Jiawei Chen, Qihao Shi, Can Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback.

Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Jingbang Chen, Yan Feng, Chun Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Location driven influence maximization: Online spread via offline deployment.

Qihao Shi, Can Wang, Jiawei Chen, Yan Feng, Chun Chen

Knowl. Based Syst., 2019

Post and repost: A holistic view of budgeted influence maximization.

Qihao Shi, Can Wang, Jiawei Chen, Yan Feng, Chun Chen

Neurocomputing, 2019

Social recommendation based on users' attention and preference.

Jiawei Chen, Can Wang, Qihao Shi, Yan Feng, Chun Chen

Neurocomputing, 2019

HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding.

Sheng Zhou, Jiajun Bu, Xin Wang, Jiawei Chen, Bingbing Hu, Defang Chen, Can Wang

CoRR, 2019

SamWalker: Social Recommendation with Informative Sampling Strategy.

Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen

Proceedings of the World Wide Web Conference, 2019

Adaptive Influence Blocking: Minimizing the Negative Spread by Observation-Based Policies.

Qihao Shi, Can Wang, Deshi Ye, Jiawei Chen, Yan Feng, Chun Chen

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018

Social Recommendation with Missing Not at Random Data.

Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, Chun Chen

Proceedings of the IEEE International Conference on Data Mining, 2018

Modeling Users' Exposure with Social Knowledge Influence and Consumption Influence for Recommendation.

Jiawei Chen, Yan Feng, Martin Ester, Sheng Zhou, Chun Chen, Can Wang

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018