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ORCIDChuan Shi 0001
Person information
- affiliation: Beijing University of Posts and Telecommunications, Beijing, China
Other persons with the same name
- Chuan Shi — disambiguation page
- Chuan Shi 0002
![[0000-0003-2564-4155]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-2564-4155")
— Beijing Liangxin Investment Management Co. Ltd. (and 1 more) - Chuan Shi 0003 — University of Maryland, College Park, MD, USA
- Chuan Shi 0004 — East China University of Science and Technology, Shanghai, China
- Chuan Shi 0005 — Xijing University, Xi'an, China
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2020 – today
- 2025
[j46]Yuxin Guo, Deyu Bo, Cheng Yang, Zhiyuan Lu, Zhongjian Zhang, Jixi Liu, Yufei Peng, Chuan Shi:
Data-Centric Graph Learning: A Survey. IEEE Trans. Big Data 11(1): 1-20 (2025)- 2024
- [j45]Qi Zhang, Cheng Yang, Chuan Shi:
Adaptive negative representations for graph contrastive learning. AI Open 5: 79-86 (2024) - [j44]Chuan Shi, Junze Chen, Jiawei Liu, Cheng Yang:
Graph foundation model. Frontiers Comput. Sci. 18(6): 186355 (2024) - [j43]Wenchuan Yang, Cheng Yang, Jichao Li, Yuejin Tan, Xin Lu, Chuan Shi:
Non-autoregressive personalized bundle generation. Inf. Process. Manag. 61(5): 103814 (2024) - [j42]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-of-Distribution Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 322-337 (2024) - [j41]Bo Yan, Cheng Yang, Chuan Shi, Yong Fang, Qi Li, Yanfang Ye, Junping Du:
Graph Mining for Cybersecurity: A Survey. ACM Trans. Knowl. Discov. Data 18(2): 47:1-47:52 (2024) - [j40]Chuan Shi, Houye Ji, Zhiyuan Lu, Ye Tang, Pan Li, Cheng Yang:
Distance Information Improves Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(3): 1030-1043 (2024) - [j39]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks With Agnostic Label Selection Bias. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4411-4422 (2024) - [j38]Chuan Shi, Meiqi Zhu, Yue Yu, Xiao Wang, Junping Du:
Unifying Graph Neural Networks with a Generalized Optimization Framework. ACM Trans. Inf. Syst. 42(6): 147:1-147:32 (2024) - [j37]Chunchen Wang, Wei Wang, Cheng Yang, Chuan Shi, Ruobing Xie, Yuanfu Lu, Haili Yang, Xu Zhang:
Group-to-group recommendation with neural graph matching. World Wide Web (WWW) 27(2): 19 (2024) - [c138]Tianrui Jia, Haoyang Li, Cheng Yang, Tao Tao, Chuan Shi:
Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization. AAAI 2024: 8562-8570 - [c137]Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi:
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization. AAAI 2024: 9241-9249 - [c136]Feng Guo, Jiawei Liu, Jianwang Zhai, Jingyu Jia, Kang Zhao, Chuan Shi:
PGAU: Static IR Drop Analysis for Power Grid using Attention U-Net Architecture and Label Distribution Smoothing. ACM Great Lakes Symposium on VLSI 2024: 452-458 - [c135]Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi:
Less is More: on the Over-Globalizing Problem in Graph Transformers. ICML 2024 - [c134]Zhiyuan Lu, Yuan Fang, Cheng Yang, Chuan Shi:
Heterogeneous Graph Transformer with Poly-Tokenization. IJCAI 2024: 2234-2242 - [c133]Fengqi Liang, Huan Zhao, Yuhan Quan, Wei Fang, Chuan Shi:
Customizing Graph Neural Network for CAD Assembly Recommendation. KDD 2024: 1746-1757 - [c132]Ruijia Wang, Haoran Dai, Cheng Yang, Le Song, Chuan Shi:
Advancing Molecule Invariant Representation via Privileged Substructure Identification. KDD 2024: 3188-3199 - [c131]Yuxin Guo, Cheng Yang, Chuan Shi, Ke Tu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou:
Adaptively Denoising Graph Neural Networks for Knowledge Distillation. ECML/PKDD (8) 2024: 253-269 - [c130]Yuanxin Zhuang, Chuan Shi, Mengmei Zhang, Jinghui Chen, Lingjuan Lyu, Pan Zhou, Lichao Sun:
Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks? USENIX Security Symposium 2024 - [c129]Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi:
Graph Fairness Learning under Distribution Shifts. WWW 2024: 676-684 - [c128]Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou:
Calibrating Graph Neural Networks from a Data-centric Perspective. WWW 2024: 745-755 - [c127]Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi:
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. WWW 2024: 1003-1014 - [c126]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. WWW 2024: 1045-1056 - [c125]Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu:
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) 2024: 1264-1267 - [c124]Bo Yan, Yang Cao, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi:
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation. WWW 2024: 3919-3929 - [i59]Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi:
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. CoRR abs/2402.07197 (2024) - [i58]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. CoRR abs/2402.12161 (2024) - [i57]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. CoRR abs/2403.02723 (2024) - [i56]Sun Ao, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong Sun, Shengnan Wang, Teng Su:
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences. CoRR abs/2403.09347 (2024) - [i55]Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi:
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization. CoRR abs/2403.12474 (2024) - [i54]Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi:
Less is More: on the Over-Globalizing Problem in Graph Transformers. CoRR abs/2405.01102 (2024) - [i53]Ao Sun, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong Sun:
Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training. CoRR abs/2406.03488 (2024) - [i52]Yuxia Wu, Shujie Li, Yuan Fang, Chuan Shi:
Exploring the Potential of Large Language Models for Heterophilic Graphs. CoRR abs/2408.14134 (2024) - [i51]Xin Li, Weize Chen, Qizhi Chu, Haopeng Li, Zhaojun Sun, Ran Li, Chen Qian, Yiwei Wei, Zhiyuan Liu, Chuan Shi, Maosong Sun, Cheng Yang:
Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models. CoRR abs/2409.19667 (2024) - 2023
- [b4]Chuan Shi, Xiao Wang, Cheng Yang:
Advances in Graph Neural Networks. Synthesis Lectures on Data Mining and Knowledge Discovery, Springer 2023, ISBN 978-3-031-16173-5, pp. 1-198 - [j36]Xiaojun Ma, Ziyao Li, Guojie Song, Chuan Shi:
Learning discrete adaptive receptive fields for graph convolutional networks. Sci. China Inf. Sci. 66(12) (2023) - [j35]Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. IEEE Trans. Big Data 9(2): 415-436 (2023) - [j34]Houye Ji, Xiao Wang, Chuan Shi, Bai Wang, Philip S. Yu:
Heterogeneous Graph Propagation Network. IEEE Trans. Knowl. Data Eng. 35(1): 521-532 (2023) - [j33]Ruijia Wang, Chuan Shi, Tianyu Zhao, Xiao Wang, Yanfang Ye:
Heterogeneous Information Network Embedding With Adversarial Disentangler. IEEE Trans. Knowl. Data Eng. 35(2): 1581-1593 (2023) - [j32]Nian Liu, Xiao Wang, Hui Han, Chuan Shi:
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35(10): 10884-10896 (2023) - [j31]Meiqi Zhu, Xiao Wang, Chuan Shi, Yibo Li, Junping Du:
Towards Adaptive Information Fusion in Graph Convolutional Networks. IEEE Trans. Knowl. Data Eng. 35(12): 13055-13069 (2023) - [j30]Cheng Yang, Hao Wang, Jian Tang, Chuan Shi, Maosong Sun, Ganqu Cui, Zhiyuan Liu:
Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2271-2283 (2023) - [j29]Yugang Ji, Chuan Shi, Yuan Fang:
Dynamic Meta-path Guided Temporal Heterogeneous Graph Neural Networks. World Sci. Annu. Rev. Artif. Intell. 1: 2350002:1-2350002:22 (2023) - [c123]Xumeng Gong, Cheng Yang, Chuan Shi:
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning. AAAI 2023: 4284-4292 - [c122]Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi:
Directed Acyclic Graph Structure Learning from Dynamic Graphs. AAAI 2023: 7512-7521 - [c121]Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi:
Retrieving GNN Architecture for Collaborative Filtering. CIKM 2023: 1379-1388 - [c120]Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi:
Node-dependent Semantic Search over Heterogeneous Graph Neural Networks. CIKM 2023: 2646-2655 - [c119]Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi:
Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks. CIKM 2023: 5346-5350 - [c118]Tianchi Yang, Haihan Gao, Cheng Yang, Chuan Shi, Qianlong Xie, Xingxing Wang, Dong Wang:
Memory-Enhanced Period-Aware Graph Neural Network for General POI Recommendation. DASFAA (2) 2023: 462-472 - [c117]Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du:
A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability. KDD 2023: 638-648 - [c116]Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi:
Graph Contrastive Learning with Stable and Scalable Spectral Encoding. NeurIPS 2023 - [c115]Ruijia Wang, YiWu Sun, Yujie Luo, Shaochuan Li, Cheng Yang, Xingyi Cheng, Hui Li, Chuan Shi, Le Song:
Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization. NeurIPS 2023 - [c114]Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi:
Provable Training for Graph Contrastive Learning. NeurIPS 2023 - [c113]Shuyun Gu, Xiao Wang, Chuan Shi:
Duplicate Multi-modal Entities Detection with Graph Contrastive Self-training Network. ECML/PKDD (2) 2023: 651-665 - [c112]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. SDM 2023: 712-720 - [c111]Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. SIGIR 2023: 2516-2520 - [c110]Yaoqi Liu, Cheng Yang, Tianyu Zhao, Hui Han, Siyuan Zhang, Jing Wu, Guangyu Zhou, Hai Huang, Hui Wang, Chuan Shi:
GammaGL: A Multi-Backend Library for Graph Neural Networks. SIGIR 2023: 2861-2870 - [c109]Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin:
Learning to Distill Graph Neural Networks. WSDM 2023: 123-131 - [c108]Hao Wang, Yao Xu, Cheng Yang, Chuan Shi, Xin Li, Ning Guo, Zhiyuan Liu:
Knowledge-Adaptive Contrastive Learning for Recommendation. WSDM 2023: 535-543 - [c107]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. WWW 2023: 251-262 - [c106]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. WWW 2023: 630-640 - [i50]Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi:
A Survey on Spectral Graph Neural Networks. CoRR abs/2302.05631 (2023) - [i49]Bo Yan, Cheng Yang, Chuan Shi, Yong Fang, Qi Li, Yanfang Ye, Junping Du:
Graph Mining for Cybersecurity: A Survey. CoRR abs/2304.00485 (2023) - [i48]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. CoRR abs/2304.00698 (2023) - [i47]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. CoRR abs/2304.01226 (2023) - [i46]Nian Liu, Xiao Wang, Hui Han, Chuan Shi:
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. CoRR abs/2304.12228 (2023) - [i45]Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi:
Provable Training for Graph Contrastive Learning. CoRR abs/2309.13944 (2023) - [i44]Cheng Yang, Deyu Bo, Jixi Liu, Yufei Peng, Boyu Chen, Haoran Dai, Ao Sun, Yue Yu, Yixin Xiao, Qi Zhang, Chunchen Wang, Yuxin Guo, Chuan Shi:
Data-centric Graph Learning: A Survey. CoRR abs/2310.04987 (2023) - [i43]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Towards Graph Foundation Models: A Survey and Beyond. CoRR abs/2310.11829 (2023) - [i42]Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. CoRR abs/2311.13864 (2023) - [i41]Tianrui Jia, Haoyang Li, Cheng Yang, Tao Tao, Chuan Shi:
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization. CoRR abs/2312.10988 (2023) - 2022
- [b3]Chuan Shi, Xiao Wang, Philip S. Yu:
Heterogeneous Graph Representation Learning and Applications. Artificial Intelligence: Foundations, Theory, and Algorithms, Springer 2022, ISBN 978-981-16-6165-5, pp. 1-318 - [j28]Jiawei Liu, Chuan Shi, Cheng Yang, Zhiyuan Lu, Philip S. Yu:
A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources. AI Open 3: 40-57 (2022) - [j27]Tianchi Yang, Luhao Zhang, Cheng Yang, Chuan Shi, Maodi Hu, Tao Li, Dong Wang:
Hypergraph Clustering Network for Interaction Data. IEEE Data Eng. Bull. 45(4): 88-101 (2022) - [j26]Jing Zhang, Qingyong Li, Yangli-ao Geng, Wen Wang, Wenju Sun, Chuan Shi, Zhengming Ding:
A zero-shot learning framework via cluster-prototype matching. Pattern Recognit. 124: 108469 (2022) - [j25]Guojie Song, Chuan Shi, Yizhou Sun, Zhiyuan Liu:
Guest Editorial: Special Issue on Social Media Computing. IEEE Trans. Big Data 8(4): 953-954 (2022) - [j24]Yiding Zhang, Xiao Wang, Chuan Shi, Xunqiang Jiang, Yanfang Ye:
Hyperbolic Graph Attention Network. IEEE Trans. Big Data 8(6): 1690-1701 (2022) - [j23]Yiding Zhang, Xiao Wang, Nian Liu, Chuan Shi:
Embedding Heterogeneous Information Network in Hyperbolic Spaces. ACM Trans. Knowl. Discov. Data 16(2): 35:1-35:23 (2022) - [j22]Chuan Shi, Yuanfu Lu, Linmei Hu, Zhiyuan Liu, Huadong Ma:
RHINE: Relation Structure-Aware Heterogeneous Information Network Embedding. IEEE Trans. Knowl. Data Eng. 34(1): 433-447 (2022) - [j21]Xiao Wang, Yuanfu Lu, Chuan Shi, Ruijia Wang, Peng Cui, Shuai Mou:
Dynamic Heterogeneous Information Network Embedding With Meta-Path Based Proximity. IEEE Trans. Knowl. Data Eng. 34(3): 1117-1132 (2022) - [c105]Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou:
Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations. AAAI 2022: 3913-3921 - [c104]Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks. AAAI 2022: 4363-4370 - [c103]Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi:
OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network. CIKM 2022: 3993-3997 - [c102]Tianchi Yang, Luhao Zhang, Chuan Shi, Cheng Yang, Siyong Xu, Ruiyu Fang, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang:
Gated Hypergraph Neural Network for Scene-Aware Recommendation. DASFAA (2) 2022: 199-215 - [c101]Luhao Zhang, Ruiyu Fang, Tianchi Yang, Maodi Hu, Tao Li, Chuan Shi, Dong Wang:
A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation. DASFAA (3) 2022: 351-363 - [c100]Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao:
Self-supervised Graph Neural Networks for Multi-behavior Recommendation. IJCAI 2022: 2052-2058 - [c99]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. IJCAI 2022: 2441-2447 - [c98]Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang:
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. NeurIPS 2022 - [c97]Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei:
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum. NeurIPS 2022 - [c96]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. NeurIPS 2022 - [c95]Yiding Zhang, Chaozhuo Li, Xing Xie, Xiao Wang, Chuan Shi, Yuming Liu, Hao Sun, Liangjie Zhang, Weiwei Deng, Qi Zhang:
Geometric Disentangled Collaborative Filtering. SIGIR 2022: 80-90 - [c94]Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang:
Co-clustering Interactions via Attentive Hypergraph Neural Network. SIGIR 2022: 859-869 - [c93]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. SIGIR 2022: 2776-2789 - [c92]Zhenyi Wang, Huan Zhao, Chuan Shi:
Profiling the Design Space for Graph Neural Networks based Collaborative Filtering. WSDM 2022: 1109-1119 - [c91]Cheng Yang, Chunchen Wang, Yuanfu Lu, Xumeng Gong, Chuan Shi, Wei Wang, Xu Zhang:
Few-shot Link Prediction in Dynamic Networks. WSDM 2022: 1245-1255 - [c90]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. WWW 2022: 1248-1258 - [c89]Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du:
Prohibited Item Detection via Risk Graph Structure Learning. WWW 2022: 1434-1443 - [c88]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. WWW 2022: 1601-1610 - [i40]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. CoRR abs/2201.05540 (2022) - [i39]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks with Agnostic Label Selection Bias. CoRR abs/2201.07708 (2022) - [i38]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. CoRR abs/2201.11349 (2022) - [i37]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. CoRR abs/2202.09177 (2022) - [i36]Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi:
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022. CoRR abs/2203.01820 (2022) - [i35]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. CoRR abs/2205.03811 (2022) - [i34]Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
KGNN: Distributed Framework for Graph Neural Knowledge Representation. CoRR abs/2205.08285 (2022) - [i33]Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang:
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. CoRR abs/2209.14107 (2022) - [i32]Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei:
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum. CoRR abs/2210.02330 (2022) - [i31]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. CoRR abs/2210.03011 (2022) - [i30]Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi:
Directed Acyclic Graph Structure Learning from Dynamic Graphs. CoRR abs/2211.17029 (2022) - [i29]Yining Wang, Xumeng Gong, Shaochuan Li, Bing Yang, YiWu Sun, Chuan Shi, Yangang Wang, Cheng Yang, Hui Li, Le Song:
xTrimoABFold: De novo Antibody Structure Prediction without MSA. CoRR abs/2212.00735 (2022) - [i28]Xumeng Gong, Cheng Yang, Chuan Shi:
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning. CoRR abs/2212.07035 (2022) - 2021
- [b2]Cheng Yang, Zhiyuan Liu, Cunchao Tu, Chuan Shi, Maosong Sun:
Network Embedding: Theories, Methods, and Applications. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2021, ISBN 978-3-031-00462-9, pp. 1-242 - [j20]Linmei Hu, Mengmei Zhang, Shaohua Li, Jinghan Shi, Chuan Shi, Cheng Yang, Zhiyuan Liu:
Text-Graph Enhanced Knowledge Graph Representation Learning. Frontiers Artif. Intell. 4: 697856 (2021) - [j19]Yugang Ji, Mingyang Yin, Hongxia Yang, Jingren Zhou, Vincent W. Zheng, Chuan Shi, Yuan Fang:
Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling. ACM Trans. Knowl. Discov. Data 15(1): 10:1-10:23 (2021) - [j18]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 33(4): 1413-1425 (2021) - [j17]Tianchi Yang, Linmei Hu, Chuan Shi, Houye Ji, Xiaoli Li, Liqiang Nie:
HGAT: Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification. ACM Trans. Inf. Syst. 39(3): 32:1-32:29 (2021) - [c87]Houye Ji, Junxiong Zhu, Xiao Wang, Chuan Shi, Bai Wang, Xiaoye Tan, Yanghua Li, Shaojian He:
Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. AAAI 2021: 232-239 - [c86]Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen:
Beyond Low-frequency Information in Graph Convolutional Networks. AAAI 2021: 3950-3957 - [c85]Yi Li, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi, Yiming Wang:
GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks. AAAI 2021: 4206-4214 - [c84]Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi:
Learning to Pre-train Graph Neural Networks. AAAI 2021: 4276-4284 - [c83]Jianan Zhao, Xiao Wang, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye:
Heterogeneous Graph Structure Learning for Graph Neural Networks. AAAI 2021: 4697-4705 - [c82]Linmei Hu, Tianchi Yang, Luhao Zhang, Wanjun Zhong, Duyu Tang, Chuan Shi, Nan Duan, Ming Zhou:
Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge. ACL/IJCNLP (1) 2021: 754-763 - [c81]Xunqiang Jiang, Yuanfu Lu, Yuan Fang, Chuan Shi:
Contrastive Pre-Training of GNNs on Heterogeneous Graphs. CIKM 2021: 803-812 - [c80]Hao Wang, Cheng Yang, Chuan Shi:
Neural Information Diffusion Prediction with Topic-Aware Attention Network. CIKM 2021: 1899-1908 - [c79]Siyong Xu, Cheng Yang, Chuan Shi, Yuan Fang, Yuxin Guo, Tianchi Yang, Luhao Zhang, Maodi Hu:
Topic-aware Heterogeneous Graph Neural Network for Link Prediction. CIKM 2021: 2261-2270 - [c78]Yugang Ji, Chuan Shi, Xiao Wang:
Prohibited Item Detection on Heterogeneous Risk Graphs. CIKM 2021: 3867-3877 - [c77]Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Chuan Shi, Philip S. Yu, Ming-Syan Chen:
Structure-Aware Parameter-Free Group Query via Heterogeneous Information Network Transformer. ICDE 2021: 2075-2080 - [c76]Houye Ji, Cheng Yang, Chuan Shi, Pan Li:
Heterogeneous Graph Neural Network with Distance Encoding. ICDM 2021: 1138-1143 - [c75]Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang:
CuCo: Graph Representation with Curriculum Contrastive Learning. IJCAI 2021: 2300-2306 - [c74]Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang:
Pre-training on Large-Scale Heterogeneous Graph. KDD 2021: 756-766 - [c73]Xiao Wang, Nian Liu, Hui Han, Chuan Shi:
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. KDD 2021: 1726-1736 - [c72]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c71]Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang:
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). KDD 2021: 4157-4158 - [c70]Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang:
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration. NeurIPS 2021: 23768-23779 - [c69]Tianchi Yang, Linmei Hu, Luhao Zhang, Chuan Shi, Cheng Yang, Nan Duan, Ming Zhou:
Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction. PAKDD (3) 2021: 325-337 - [c68]Yuanxin Zhuang, Chuan Shi, Cheng Yang, Fuzhen Zhuang, Yangqiu Song:
Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation. ECML/PKDD (2) 2021: 335-350 - [c67]Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi:
Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process. ECML/PKDD (1) 2021: 388-403 - [c66]Chen Li, Linmei Hu, Chuan Shi, Guojie Song, Yuanfu Lu:
Sequence-aware Heterogeneous Graph Neural Collaborative Filtering. SDM 2021: 64-72 - [c65]Chen Li, Yuanfu Lu, Wei Wang, Chuan Shi, Ruobing Xie, Haili Yang, Cheng Yang, Xu Zhang, Leyu Lin:
Package Recommendation with Intra- and Inter-Package Attention Networks. SIGIR 2021: 595-604 - [c64]Ruijia Wang, Shuai Mou, Xiao Wang, Wanpeng Xiao, Qi Ju, Chuan Shi, Xing Xie:
Graph Structure Estimation Neural Networks. WWW 2021: 342-353 - [c63]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. WWW 2021: 1215-1226 - [c62]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. WWW 2021: 1227-1237 - [c61]Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song:
Lorentzian Graph Convolutional Networks. WWW 2021: 1249-1261 - [c60]Houye Ji, Junxiong Zhu, Chuan Shi, Xiao Wang, Bai Wang, Chaoyu Zhang, Zixuan Zhu, Feng Zhang, Yanghua Li:
Large-scale Comb-K Recommendation. WWW 2021: 2512-2523 - [i27]Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen:
Beyond Low-frequency Information in Graph Convolutional Networks. CoRR abs/2101.00797 (2021) - [i26]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. CoRR abs/2101.11859 (2021) - [i25]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. CoRR abs/2103.02885 (2021) - [i24]Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song:
Lorentzian Graph Convolutional Networks. CoRR abs/2104.07477 (2021) - [i23]Xiao Wang, Nian Liu, Hui Han, Chuan Shi:
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. CoRR abs/2105.09111 (2021) - [i22]Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang:
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration. CoRR abs/2109.14285 (2021) - [i21]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs. CoRR abs/2111.10657 (2021) - 2020
- [j16]Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, Chao Shao:
Graph neural news recommendation with long-term and short-term interest modeling. Inf. Process. Manag. 57(2): 102142 (2020) - [j15]Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin:
Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. 57(6): 102338 (2020) - [c59]Yilun Jin, Guojie Song, Chuan Shi:
GraLSP: Graph Neural Networks with Local Structural Patterns. AAAI 2020: 4361-4368 - [c58]Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li:
Multi-Component Graph Convolutional Collaborative Filtering. AAAI 2020: 6267-6274 - [c57]Linmei Hu, Siyong Xu, Chen Li, Cheng Yang, Chuan Shi, Nan Duan, Xing Xie, Ming Zhou:
Graph Neural News Recommendation with Unsupervised Preference Disentanglement. ACL 2020: 4255-4264 - [c56]Jing Zhang, Yangli-ao Geng, Qingyong Li, Chuan Shi:
More Than One: A Cluster-Prototype Matching Framework for Zero-Shot Learning. CIKM 2020: 1803-1812 - [c55]Zhiqiang Zhang, Jun Zhou, Chuan Shi:
EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning. CIKM 2020: 3485-3488 - [c54]Yiming Zhang, Yujie Fan, Shifu Hou, Yanfang Ye, Xusheng Xiao, Pan Li, Chuan Shi, Liang Zhao, Shouhuai Xu:
Cyber-guided Deep Neural Network for Malicious Repository Detection in GitHub. ICKG 2020: 458-465 - [c53]Yujie Fan, Yanfang Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, Liang Zhao:
Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. ICDM 2020: 132-141 - [c52]Mengmei Zhang, Linmei Hu, Chuan Shi, Xiao Wang:
Adversarial Label-Flipping Attack and Defense for Graph Neural Networks. ICDM 2020: 791-800 - [c51]Junshan Wang, Ziyao Li, Qingqing Long, Weiyu Zhang, Guojie Song, Chuan Shi:
Learning Node Representations from Noisy Graph Structures. ICDM 2020: 1310-1315 - [c50]Jianan Zhao, Xiao Wang, Chuan Shi, Zekuan Liu, Yanfang Ye:
Network Schema Preserving Heterogeneous Information Network Embedding. IJCAI 2020: 1366-1372 - [c49]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. IJCAI 2020: 2177-2183 - [c48]Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. KDD 2020: 1243-1253 - [c47]Yuanfu Lu, Yuan Fang, Chuan Shi:
Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. KDD 2020: 1563-1573 - [c46]Yuanfu Lu, Ruobing Xie, Chuan Shi, Yuan Fang, Wei Wang, Xu Zhang, Leyu Lin:
Social Influence Attentive Neural Network for Friend-Enhanced Recommendation. ECML/PKDD (4) 2020: 3-18 - [c45]Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi:
Temporal Heterogeneous Interaction Graph Embedding for Next-Item Recommendation. ECML/PKDD (3) 2020: 314-329 - [c44]Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi:
Multiplex Memory Network for Collaborative Filtering. SDM 2020: 91-99 - [c43]Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui:
Structural Deep Clustering Network. WWW 2020: 1400-1410 - [c42]Shaohua Fan, Xiao Wang, Chuan Shi, Emiao Lu, Ken Lin, Bai Wang:
One2Multi Graph Autoencoder for Multi-view Graph Clustering. WWW 2020: 3070-3076 - [i20]Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui:
Structural Deep Clustering Network. CoRR abs/2002.01633 (2020) - [i19]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. CoRR abs/2006.15874 (2020) - [i18]Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. CoRR abs/2007.02265 (2020) - [i17]Jinghan Shi, Houye Ji, Chuan Shi, Xiao Wang, Zhiqiang Zhang, Jun Zhou:
Heterogeneous Graph Neural Network for Recommendation. CoRR abs/2009.00799 (2020) - [i16]Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. CoRR abs/2011.14867 (2020) - [i15]Junshan Wang, Ziyao Li, Qingqing Long, Weiyu Zhang, Guojie Song, Chuan Shi:
Learning Node Representations from Noisy Graph Structures. CoRR abs/2012.02434 (2020)
2010 – 2019
- 2019
- [j14]Chuan Shi, Binbin Hu, Wayne Xin Zhao, Philip S. Yu:
Heterogeneous Information Network Embedding for Recommendation. IEEE Trans. Knowl. Data Eng. 31(2): 357-370 (2019) - [j13]Chuan Shi, Zhiqiang Zhang, Yugang Ji, Weipeng Wang, Philip S. Yu, Zhiping Shi:
SemRec: a personalized semantic recommendation method based on weighted heterogeneous information networks. World Wide Web 22(1): 153-184 (2019) - [c41]Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi:
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism. AAAI 2019: 946-953 - [c40]Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu:
Relation Structure-Aware Heterogeneous Information Network Embedding. AAAI 2019: 4456-4463 - [c39]Xiao Wang, Yiding Zhang, Chuan Shi:
Hyperbolic Heterogeneous Information Network Embedding. AAAI 2019: 5337-5344 - [c38]Jianan Zhao, Ding Xiao, Linmei Hu, Chuan Shi:
Coupled Semi-supervised Clustering: Exploring Attribute Correlations in Heterogeneous Information Networks. APWeb/WAIM (1) 2019: 95-109 - [c37]Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye:
Temporal Network Embedding with Micro- and Macro-dynamics. CIKM 2019: 469-478 - [c36]Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Chuan Shi:
Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework. CIKM 2019: 549-558 - [c35]Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye:
Author Set Identification via Quasi-Clique Discovery. CIKM 2019: 771-780 - [c34]Chuan Shi, Philip S. Yu:
Recent Developments of Deep Heterogeneous Information Network Analysis. CIKM 2019: 2973-2974 - [c33]Chuan Shi, Yanfang Ye, Jiawei Zhang:
HENA 2019: The 3rd Workshop of Heterogeneous Information Network Analysis and Applications. CIKM 2019: 2991-2992 - [c32]Linmei Hu, Luhao Zhang, Chuan Shi, Liqiang Nie, Weili Guan, Cheng Yang:
Improving Distantly-Supervised Relation Extraction with Joint Label Embedding. EMNLP/IJCNLP (1) 2019: 3819-3827 - [c31]Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu:
iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. IJCAI 2019: 2272-2278 - [c30]Binbin Hu, Yuan Fang, Chuan Shi:
Adversarial Learning on Heterogeneous Information Networks. KDD 2019: 120-129 - [c29]Yugang Ji, Chuan Shi, Fuzhen Zhuang, Philip S. Yu:
Integrating Topic Model and Heterogeneous Information Network for Aspect Mining with Rating Bias. PAKDD (1) 2019: 160-171 - [c28]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Yanfang Ye, Peng Cui, Philip S. Yu:
Heterogeneous Graph Attention Network. WWW 2019: 2022-2032 - [c27]Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong:
Your Style Your Identity: Leveraging Writing and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network. WWW 2019: 3448-3454 - [i14]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, Philip S. Yu, Yanfang Ye:
Heterogeneous Graph Attention Network. CoRR abs/1903.07293 (2019) - [i13]Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu:
Relation Structure-Aware Heterogeneous Information Network Embedding. CoRR abs/1905.08027 (2019) - [i12]Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye:
Temporal Network Embedding with Micro- and Macro-dynamics. CoRR abs/1909.04246 (2019) - [i11]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. CoRR abs/1909.06627 (2019) - [i10]Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, Chao Shao:
Graph Neural News Recommendation with Long-term and Short-term Interest Modeling. CoRR abs/1910.14025 (2019) - [i9]Yilun Jin, Guojie Song, Chuan Shi:
GraLSP: Graph Neural Networks with Local Structural Patterns. CoRR abs/1911.07675 (2019) - [i8]Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li:
Multi-Component Graph Convolutional Collaborative Filtering. CoRR abs/1911.10699 (2019) - [i7]Yiding Zhang, Xiao Wang, Xunqiang Jiang, Chuan Shi, Yanfang Ye:
Hyperbolic Graph Attention Network. CoRR abs/1912.03046 (2019) - 2018
- [j12]Ding Xiao, Yugang Ji, Yitong Li, Fuzhen Zhuang, Chuan Shi:
Coupled matrix factorization and topic modeling for aspect mining. Inf. Process. Manag. 54(6): 861-873 (2018) - [j11]Fuzhen Zhuang, Jing Zheng, Jingwu Chen, Xiangliang Zhang, Chuan Shi, Qing He:
Transfer collaborative filtering from multiple sources via consensus regularization. Neural Networks 108: 287-295 (2018) - [j10]Chuan Shi, Jian Liu, Yiding Zhang, Binbin Hu, Shenghua Liu, Philip S. Yu:
MFPR: A Personalized Ranking Recommendation with Multiple Feedback. ACM Trans. Soc. Comput. 1(2): 7:1-7:22 (2018) - [c26]Menghao Zhang, Binbin Hu, Chuan Shi, Bin Wu, Bai Wang:
Matrix Factorization Meets Social Network Embedding for Rating Prediction. APWeb/WAIM (1) 2018: 121-129 - [c25]Xiaotian Han, Chuan Shi, Lei Zheng, Philip S. Yu, Jianxin Li, Yuanfu Lu:
Representation Learning with Depth and Breadth for Recommendation Using Multi-view Data. APWeb/WAIM (1) 2018: 181-188 - [c24]Shaohua Fan, Chuan Shi, Xiao Wang:
Abnormal Event Detection via Heterogeneous Information Network Embedding. CIKM 2018: 1483-1486 - [c23]Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang, Xueqi Cheng:
NeuCast: Seasonal Neural Forecast of Power Grid Time Series. IJCAI 2018: 3315-3321 - [c22]Xiaotian Han, Chuan Shi, Senzhang Wang, Philip S. Yu, Li Song:
Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. IJCAI 2018: 3393-3399 - [c21]Binbin Hu, Chuan Shi, Wayne Xin Zhao, Philip S. Yu:
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model. KDD 2018: 1531-1540 - [c20]Houye Ji, Chuan Shi, Bai Wang:
Attention Based Meta Path Fusion for Heterogeneous Information Network Embedding. PRICAI (1) 2018: 348-360 - 2017
- [b1]Chuan Shi, Philip S. Yu:
Heterogeneous Information Network Analysis and Applications. Data Analytics, Springer 2017, ISBN 978-3-319-56211-7, pp. 1-227 - [j9]Jing Zheng, Jian Liu, Chuan Shi, Fuzhen Zhuang, Jingzhi Li, Bin Wu:
Recommendation in heterogeneous information network via dual similarity regularization. Int. J. Data Sci. Anal. 3(1): 35-48 (2017) - [j8]Fuzhen Zhuang, Zhiqiang Zhang, Mingda Qian, Chuan Shi, Xing Xie, Qing He:
Representation learning via Dual-Autoencoder for recommendation. Neural Networks 90: 83-89 (2017) - [j7]Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, Philip S. Yu:
A Survey of Heterogeneous Information Network Analysis. IEEE Trans. Knowl. Data Eng. 29(1): 17-37 (2017) - [c19]Jing Zheng, Fuzhen Zhuang, Chuan Shi:
Local Ensemble across Multiple Sources for Collaborative Filtering. CIKM 2017: 2431-2434 - [c18]Jian Liu, Chuan Shi, Binbin Hu, Shenghua Liu, Philip S. Yu:
Personalized Ranking Recommendation via Integrating Multiple Feedbacks. PAKDD (2) 2017: 131-143 - [c17]Menghao Zhang, Binbin Hu, Chuan Shi, Bai Wang:
Local Low-Rank Matrix Approximation with Preference Selection of Anchor Points. WWW (Companion Volume) 2017: 1395-1403 - [i6]Chuan Shi, Binbin Hu, Wayne Xin Zhao, Philip S. Yu:
Heterogeneous Information Network Embedding for Recommendation. CoRR abs/1711.10730 (2017) - 2016
- [j6]Chuan Shi, Yitong Li, Philip S. Yu, Bin Wu:
Constrained-meta-path-based ranking in heterogeneous information network. Knowl. Inf. Syst. 49(2): 719-747 (2016) - [j5]Chuan Shi, Jian Liu, Fuzhen Zhuang, Philip S. Yu, Bin Wu:
Integrating heterogeneous information via flexible regularization framework for recommendation. Knowl. Inf. Syst. 49(3): 835-859 (2016) - [c16]Chuan Shi, Bowei He, Menghao Zhang, Fuzhen Zhuang, Philip S. Yu, Naiwang Guo:
Expenditure aware rating prediction for recommendation. IEEE BigData 2016: 1018-1025 - [c15]Jing Zheng, Jian Liu, Chuan Shi, Fuzhen Zhuang, Jingzhi Li, Bin Wu:
Dual Similarity Regularization for Recommendation. PAKDD (2) 2016: 542-554 - [c14]Yitong Li, Chuan Shi, Huidong Zhao, Fuzhen Zhuang, Bin Wu:
Aspect Mining with Rating Bias. ECML/PKDD (2) 2016: 458-474 - [c13]Jiawei Hu, Zhiqiang Zhang, Jian Liu, Chuan Shi, Philip S. Yu, Bai Wang:
RecExp: A Semantic Recommender System with Explanation Based on Heterogeneous Information Network. RecSys 2016: 401-402 - [i5]Chuan Shi, Bowei He, Menghao Zhang, Fuzhen Zhuang, Philip S. Yu:
Expenditure Aware Rating Prediction for Recommendation. CoRR abs/1610.05464 (2016) - 2015
- [c12]Chuan Shi, Zhiqiang Zhang, Ping Luo, Philip S. Yu, Yading Yue, Bin Wu:
Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks. CIKM 2015: 453-462 - [i4]Chuan Shi, Jian Liu, Fuzhen Zhuang, Philip S. Yu, Bin Wu:
Integrating Heterogeneous Information via Flexible Regularization Framework for Recommendation. CoRR abs/1511.03759 (2015) - [i3]Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, Philip S. Yu:
A Survey of Heterogeneous Information Network Analysis. CoRR abs/1511.04854 (2015) - 2014
- [j4]Chuan Shi, Philip S. Yu, Zhenyu Yan, Yue Huang, Bai Wang:
Comparison and Selection of objective Functions in multiobjective Community Detection. Comput. Intell. 30(3): 562-582 (2014) - [j3]Chuan Shi, Xiangnan Kong, Di Fu, Philip S. Yu, Bin Wu:
Multi-Label Classification Based on Multi-Objective Optimization. ACM Trans. Intell. Syst. Technol. 5(2): 35:1-35:22 (2014) - [j2]Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu:
HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 26(10): 2479-2492 (2014) - [c11]Chuan Shi, Ran Wang, Yitong Li, Philip S. Yu, Bin Wu:
Ranking-based Clustering on General Heterogeneous Information Networks by Network Projection. CIKM 2014: 699-708 - [c10]Yitong Li, Chuan Shi, Philip S. Yu, Qing Chen:
HRank: A Path Based Ranking Method in Heterogeneous Information Network. WAIM 2014: 553-565 - [i2]Yitong Li, Chuan Shi, Philip S. Yu, Qing Chen:
HRank: A Path based Ranking Framework in Heterogeneous Information Network. CoRR abs/1403.7315 (2014) - 2013
- [c9]Ran Wang, Chuan Shi, Philip S. Yu, Bin Wu:
Integrating Clustering and Ranking on Hybrid Heterogeneous Information Network. PAKDD (1) 2013: 583-594 - [i1]Chuan Shi, Xiangnan Kong, Yue Huang, Philip S. Yu, Bin Wu:
HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks. CoRR abs/1309.7393 (2013) - 2012
- [c8]Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie, Bin Wu:
Relevance search in heterogeneous networks. EDBT 2012: 180-191 - [c7]Chuan Shi, Chong Zhou, Xiangnan Kong, Philip S. Yu, Gang Liu, Bai Wang:
HeteRecom: a semantic-based recommendation systemin heterogeneous networks. KDD 2012: 1552-1555 - [c6]Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang:
Multi-Objective Multi-Label Classification. SDM 2012: 355-366 - 2011
- [c5]Chuan Shi, Philip S. Yu, Yanan Cai, Zhenyu Yan, Bin Wu:
On selection of objective functions in multi-objective community detection. CIKM 2011: 2301-2304 - [c4]Chuan Shi, Xiangnan Kong, Philip S. Yu, Bai Wang:
Multi-label Ensemble Learning. ECML/PKDD (3) 2011: 223-239 - 2010
- [c3]Zhiyuan Liu, Chuan Shi, Maosong Sun:
FolkDiffusion: A Graph-Based Tag Suggestion Method for Folksonomies. AIRS 2010: 231-240 - [c2]Chuan Shi, Yanan Cai, Philip S. Yu, Zhenyu Yan, Bin Wu:
A Comparison of Objective Functions in Network Community Detection. ICDM Workshops 2010: 1234-1241
2000 – 2009
- 2009
- [j1]Chuan Shi, Zhenyu Yan, Kevin Lü, Zhongzhi Shi, Bai Wang:
A dominance tree and its application in evolutionary multi-objective optimization. Inf. Sci. 179(20): 3540-3560 (2009) - 2006
- [c1]Chuan Shi, Qingyong Li, Zhiyong Zhang, Zhongzhi Shi:
An Improved Multiobjective Evolutionary Algorithm Based on Dominating Tree. PRICAI 2006: 691-700
Coauthor Index
[j42] [j39] [j38] [c135] [c129] [i54] [b4] [j35] [j34] [j33] [j32] [j31] [c122] [c114] [c113] [c106] [i50] [i46] [i45] [b3] [j24] [j23] [j21] [c105] [c104] [c103] [c100] [c98] [c97] [c96] [c95] [c93] [c90] [c89] [c88] [i40] [i39] [i38] [i37] [i33] [i32] [i31] [i30] [j18] [c87] [c86] [c83] [c78] [c75] [c73] [c70] [c64] [c63] [c61] [c60] [i27] [i26] [i24] [i23] [i22] [i21] [c58] [c52] [c50] [c49] [c48] [c43] [c42] [i20] [i19] [i18] [i17] [i16] [c39] [c37] [c28] [i14] [i12] [i11] [i8] [i7] [c24]
[j46] [j45] [j43] [j41] [j40] [j37] [c138] [c137] [c134] [c132] [c131] [c128] [c127] [c126] [c125] [i59] [i58] [i56] [i55] [i53] [i51] [b4] [j30] [c123] [c119] [c118] [c117] [c115] [c112] [c110] [c109] [c108] [c107] [i49] [i48] [i47] [i44] [i41] [j28] [j27] [c103] [c102] [c94] [c93] [c91] [i37] [i29] [i28] [b2] [j20] [c80] [c79] [c76] [c70] [c69] [c68] [c65] [c62] [i25] [i22] [j16] [c57] [c32] [i10]
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