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ORCIDChao Huang 0001
Person information
- affiliation: University of Hong Kong, Department of Computer Science, Data Mining and Intelligence Lab@HKU, Hong Kong
- affiliation: JD Finance America Corporation, Mountain View, CA, USA
- affiliation: University of Notre Dame, Department of Computer Science and Engineering, IN, USA
Other persons with the same name
- Chao Huang — disambiguation page
- Chao Huang 0002
![[0000-0002-8012-3697]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-8012-3697")
— University of Science and Technology Beijing, School of Computer and Communication Engineering, China (and 2 more) - Chao Huang 0003 — University of Electronic Science and Technology of China, School of Electronic Engineering, Chengdu, China
- Chao Huang 0004 — Shenzhen University, College of Mathematics and Statistics, China (and 1 more)
- Chao Huang 0005 — Florida State University, Department of Statistics, Tallahassee, FL, USA (and 2 more)
- Chao Huang 0006 — Hong Kong Polytechnic University, Department of Industrial and Systems Engineering, Hong Kong (and 2 more)
- Chao Huang 0007 — Nanjing Audit University, Institute for Social and Economic Research, China (and 1 more)
- Chao Huang 0008 — Harbin Institute of Technology, Shenzhen, China (and 1 more)
- Chao Huang 0009 — Zhejiang University, School of Public Health / Women's Hospital School of Medicine, Hangzhou, China (and 1 more)
- Chao Huang 0010 — Fujian Normal University, College of Mathematics and Informatics / Digital Fujian Internet-of-Things Laboratory of Environmental Monitoring , Fuzhou, China
- Chao Huang 0011 — Microsoft Research Asia, Beijing, China
- Chao Huang 0012 — Beihang University, School of Cyber Science and Technology, Beijing, China (and 1 more)
- Chao Huang 0013 — University of Tokyo, Department of Mechanical Engineering, Japan (and 1 more)
- Chao Huang 0014 — National Institute of Informatics, Tokyo, Japan (and 1 more)
- Chao Huang 0015 — University of Liverpool, Department of Computer Science, Liverpool, UK (and 1 more)
- Chao Huang 0016 — Tencent Hippocrates Research Lab, Palo Alto, CA, USA (and 2 more)
- Chao Huang 0017 — Tianjin University of Technology, China
- Chao Huang 0018 — Tongji University, Department of Control Science and Engineering, Shanghai Institute of Intelligent Science and Technology, Shanghai, China (and 3 more)
- Chao Huang 0019 — Chinese Academy of Sciences, Shanghai Astronomical Observatory, Shanghai, China (and 1 more)
- Chao Huang 0020 — Kyoto University, Disaster Prevention Research Institute, Kyoto, Japan
- Chao Huang 0021 — Nanjing Normal University, School of Electrical and Automation Engineering, Nanjing, China
- Chao Huang 0022 — Jinzhou Medical University, Medical Department of the First Affiliated Hospital, Jinzhou, China
- Chao Huang 0023 — Wuhan University, School of Geodesy and Geomatics, Wuhan, China
- Chao Huang 0024 — Xiamen Great Power Geo Information Technology Company Ltd., Xiamen, China
- Chao Huang 0025 — Chongqing University of Science and Technology, School of Safety Engineering, Chongqing, China
- Chao Huang 0026 — Alibaba Group (and 1 more)
- Chao Huang 0027 — Kent State University, Cognitive Robotics and AI Lab, CRAI, College of Aeronautics and Engineering, OH, USA
- Chao Huang 0028 — UC Davis, Department of Computer Science, CA, USA (and 1 more)
- Chao Huang 0029 — University of Illinois, Urbana-Champaign, Department of Computer Science, Thomas M.Siebel Center, Department of Computer Science, Urbana, IL, USA
- Chao Huang 0030 — Northwest A&F University, Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Yangling, China,
- Chao Huang 0031 — Jiangxi Agricultural University, College of Forestry, Nanchang, China (and 1 more)
- Chao Huang 0032 — Chinese Academy of Sciences, Shanghai Advanced Research Institute, China (and 1 more)
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2020 – today
- 2024
[j18]Chaofan Fu, Pengyang Yu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong:
MHGCN+: Multiplex Heterogeneous Graph Convolutional Network. ACM Trans. Intell. Syst. Technol. 15(3): 51:1-51:25 (2024)- [j17]Wei Chen, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong:
Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks. ACM Trans. Knowl. Discov. Data 18(4): 85:1-85:22 (2024) - [j16]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo:
Multi-Behavior Graph Neural Networks for Recommender System. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5473-5487 (2024) - [j15]Shuzhe Li, Wei Chen, Bin Wang, Chao Huang, Yanwei Yu, Junyu Dong:
MCN4Rec: Multi-level Collaborative Neural Network for Next Location Recommendation. ACM Trans. Inf. Syst. 42(4): 105:1-105:26 (2024) - [c106]Qianru Zhang, Lianghao Xia, Xuheng Cai, Siu-Ming Yiu, Chao Huang, Christian S. Jensen:
Graph Augmentation for Recommendation. ICDE 2024: 557-569 - [c105]Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang:
GraphGPT: Graph Instruction Tuning for Large Language Models. SIGIR 2024: 491-500 - [c104]Yuxi Liu, Lianghao Xia, Chao Huang:
SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation. SIGIR 2024: 1609-1618 - [c103]Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang:
DiffKG: Knowledge Graph Diffusion Model for Recommendation. WSDM 2024: 313-321 - [c102]Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang:
SSLRec: A Self-Supervised Learning Framework for Recommendation. WSDM 2024: 567-575 - [c101]Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang:
LLMRec: Large Language Models with Graph Augmentation for Recommendation. WSDM 2024: 806-815 - [c100]Chao Huang, Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla:
Large Language Models for Graphs: Progresses and Directions. WWW (Companion Volume) 2024: 1284-1287 - [c99]Wei Wei, Jiabin Tang, Lianghao Xia, Yangqin Jiang, Chao Huang:
PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning. WWW 2024: 3217-3228 - [c98]Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang:
Representation Learning with Large Language Models for Recommendation. WWW 2024: 3464-3475 - [c97]Yuhao Yang, Lianghao Xia, Da Luo, Kangyi Lin, Chao Huang:
GraphPro: Graph Pre-training and Prompt Learning for Recommendation. WWW 2024: 3690-3699 - [i75]Zirui Guo, Lianghao Xia, Yanhua Yu, Yuling Wang, Zixuan Yang, Wei Wei, Liang Pang, Tat-Seng Chua, Chao Huang:
GraphEdit: Large Language Models for Graph Structure Learning. CoRR abs/2402.15183 (2024) - [i74]Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, Chao Huang:
HiGPT: Heterogeneous Graph Language Model. CoRR abs/2402.16024 (2024) - [i73]Wei Wei, Jiabin Tang, Yangqin Jiang, Lianghao Xia, Chao Huang:
PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning. CoRR abs/2402.17188 (2024) - [i72]Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang:
UrbanGPT: Spatio-Temporal Large Language Models. CoRR abs/2403.00813 (2024) - [i71]Lianghao Xia, Ben Kao, Chao Huang:
OpenGraph: Towards Open Graph Foundation Models. CoRR abs/2403.01121 (2024) - [i70]Xiang Li, Chaofan Fu, Zhongying Zhao, Guanjie Zheng, Chao Huang, Junyu Dong, Yanwei Yu:
Dual-Channel Multiplex Graph Neural Networks for Recommendation. CoRR abs/2403.11624 (2024) - [i69]Qianru Zhang, Lianghao Xia, Xuheng Cai, Siu-Ming Yiu, Chao Huang, Christian S. Jensen:
Graph Augmentation for Recommendation. CoRR abs/2403.16656 (2024) - [i68]Xubin Ren, Wei Wei, Lianghao Xia, Chao Huang:
A Comprehensive Survey on Self-Supervised Learning for Recommendation. CoRR abs/2404.03354 (2024) - [i67]Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla, Chao Huang:
A Survey of Large Language Models for Graphs. CoRR abs/2405.08011 (2024) - [i66]Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang:
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction. CoRR abs/2405.17898 (2024) - [i65]Yuxi Liu, Lianghao Xia, Chao Huang:
SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation. CoRR abs/2405.20878 (2024) - [i64]Zongwei Li, Lianghao Xia, Chao Huang:
RecDiff: Diffusion Model for Social Recommendation. CoRR abs/2406.01629 (2024) - [i63]Qiyao Ma, Xubin Ren, Chao Huang:
XRec: Large Language Models for Explainable Recommendation. CoRR abs/2406.02377 (2024) - [i62]Yangqin Jiang, Lianghao Xia, Wei Wei, Da Luo, Kangyi Lin, Chao Huang:
DiffMM: Multi-Modal Diffusion Model for Recommendation. CoRR abs/2406.11781 (2024) - 2023
- [j14]Yunfei Shi, Bin Wang, Yanwei Yu, Xianfeng Tang, Chao Huang, Junyu Dong:
Robust anomaly detection for multivariate time series through temporal GCNs and attention-based VAE. Knowl. Based Syst. 275: 110725 (2023) - [j13]Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, Junyu Dong:
Dynamic Multi-View Graph Neural Networks for Citywide Traffic Inference. ACM Trans. Knowl. Discov. Data 17(4): 53:1-53:22 (2023) - [j12]Lianghao Xia, Chao Huang, Yong Xu, Jian Pei:
Multi-Behavior Sequential Recommendation With Temporal Graph Transformer. IEEE Trans. Knowl. Data Eng. 35(6): 6099-6112 (2023) - [c96]Jiahao Ji, Jingyuan Wang, Chao Huang, Junjie Wu, Boren Xu, Zhenhe Wu, Junbo Zhang, Yu Zheng:
Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction. AAAI 2023: 4356-4364 - [c95]Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong:
Graph Structure Learning on User Mobility Data for Social Relationship Inference. AAAI 2023: 4578-4586 - [c94]Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang:
How Expressive are Graph Neural Networks in Recommendation? CIKM 2023: 173-182 - [c93]Jiabin Tang, Lianghao Xia, Jie Hu, Chao Huang:
Spatio-Temporal Meta Contrastive Learning. CIKM 2023: 2412-2421 - [c92]Jiabin Tang, Lianghao Xia, Chao Huang:
Explainable Spatio-Temporal Graph Neural Networks. CIKM 2023: 2432-2441 - [c91]Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi:
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning. ICDE 2023: 246-258 - [c90]Lianghao Xia, Yizhen Shao, Chao Huang, Yong Xu, Huance Xu, Jian Pei:
Disentangled Graph Social Recommendation. ICDE 2023: 2332-2344 - [c89]Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren:
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. ICLR 2023 - [c88]Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang:
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations. ICML 2023: 41133-41150 - [c87]Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu Ming Yiu, Ruihua Han:
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation. ICML 2023: 41151-41163 - [c86]Tianle Wang, Lianghao Xia, Chao Huang:
Denoised Self-Augmented Learning for Social Recommendation. IJCAI 2023: 2324-2331 - [c85]Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong:
Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling. KDD 2023: 482-494 - [c84]Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang:
Knowledge Graph Self-Supervised Rationalization for Recommendation. KDD 2023: 3046-3056 - [c83]Yangqin Jiang, Chao Huang, Lianghao Huang:
Adaptive Graph Contrastive Learning for Recommendation. KDD 2023: 4252-4261 - [c82]Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang:
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks. NeurIPS 2023 - [c81]Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann:
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. NeurIPS 2023 - [c80]Wei Wei, Lianghao Xia, Chao Huang:
Multi-Relational Contrastive Learning for Recommendation. RecSys 2023: 338-349 - [c79]Yaowen Ye, Lianghao Xia, Chao Huang:
Graph Masked Autoencoder for Sequential Recommendation. SIGIR 2023: 321-330 - [c78]Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, Chao Huang:
Disentangled Contrastive Collaborative Filtering. SIGIR 2023: 1137-1146 - [c77]Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang:
Graph Transformer for Recommendation. SIGIR 2023: 1680-1689 - [c76]Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo:
Heterogeneous Graph Contrastive Learning for Recommendation. WSDM 2023: 544-552 - [c75]Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu:
Graph-less Collaborative Filtering. WWW 2023: 17-27 - [c74]Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang:
Fair Graph Representation Learning via Diverse Mixture-of-Experts. WWW 2023: 28-38 - [c73]Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, Siu-Ming Yiu:
Automated Spatio-Temporal Graph Contrastive Learning. WWW 2023: 295-305 - [c72]Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang:
Multi-Modal Self-Supervised Learning for Recommendation. WWW 2023: 790-800 - [c71]Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu, Ben Kao:
Automated Self-Supervised Learning for Recommendation. WWW 2023: 992-1002 - [c70]Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo, Kangyi Lin:
Debiased Contrastive Learning for Sequential Recommendation. WWW 2023: 1063-1073 - [i61]Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann:
Do We Really Need Graph Neural Networks for Traffic Forecasting? CoRR abs/2301.12603 (2023) - [i60]Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren:
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. CoRR abs/2302.08191 (2023) - [i59]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo:
Multi-Behavior Graph Neural Networks for Recommender System. CoRR abs/2302.08678 (2023) - [i58]Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang:
Multi-Modal Self-Supervised Learning for Recommendation. CoRR abs/2302.10632 (2023) - [i57]Wei Chen, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong:
Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks. CoRR abs/2302.10903 (2023) - [i56]Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo:
Heterogeneous Graph Contrastive Learning for Recommendation. CoRR abs/2303.00995 (2023) - [i55]Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu, Ben Kao:
Automated Self-Supervised Learning for Recommendation. CoRR abs/2303.07797 (2023) - [i54]Lianghao Xia, Yizhen Shao, Chao Huang, Yong Xu, Huance Xu, Jian Pei:
Disentangled Graph Social Recommendation. CoRR abs/2303.07810 (2023) - [i53]Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu:
Graph-less Collaborative Filtering. CoRR abs/2303.08537 (2023) - [i52]Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo, Kangyi Lin:
Debiased Contrastive Learning for Sequential Recommendation. CoRR abs/2303.11780 (2023) - [i51]Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, Chao Huang:
Disentangled Contrastive Collaborative Filtering. CoRR abs/2305.02759 (2023) - [i50]Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, Siu-Ming Yiu:
Automated Spatio-Temporal Graph Contrastive Learning. CoRR abs/2305.03920 (2023) - [i49]Yaowen Ye, Lianghao Xia, Chao Huang:
Graph Masked Autoencoder for Sequential Recommendation. CoRR abs/2305.04619 (2023) - [i48]Yangqin Jiang, Chao Huang, Lianghao Xia:
Adaptive Graph Contrastive Learning for Recommendation. CoRR abs/2305.10837 (2023) - [i47]Tianle Wang, Lianghao Xia, Chao Huang:
Denoised Self-Augmented Learning for Social Recommendation. CoRR abs/2305.12685 (2023) - [i46]Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang:
Graph Transformer for Recommendation. CoRR abs/2306.02330 (2023) - [i45]Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann:
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. CoRR abs/2306.08259 (2023) - [i44]Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu-Ming Yiu, Ruihua Han:
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation. CoRR abs/2306.10683 (2023) - [i43]Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang:
Knowledge Graph Self-Supervised Rationalization for Recommendation. CoRR abs/2307.02759 (2023) - [i42]Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang:
SSLRec: A Self-Supervised Learning Library for Recommendation. CoRR abs/2308.05697 (2023) - [i41]Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang:
How Expressive are Graph Neural Networks in Recommendation? CoRR abs/2308.11127 (2023) - [i40]Wei Wei, Lianghao Xia, Chao Huang:
Multi-Relational Contrastive Learning for Recommendation. CoRR abs/2309.01103 (2023) - [i39]Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang:
GraphGPT: Graph Instruction Tuning for Large Language Models. CoRR abs/2310.13023 (2023) - [i38]Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang:
Representation Learning with Large Language Models for Recommendation. CoRR abs/2310.15950 (2023) - [i37]Jiabin Tang, Lianghao Xia, Chao Huang:
Explainable Spatio-Temporal Graph Neural Networks. CoRR abs/2310.17149 (2023) - [i36]Jiabin Tang, Lianghao Xia, Jie Hu, Chao Huang:
Spatio-Temporal Meta Contrastive Learning. CoRR abs/2310.17678 (2023) - [i35]Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang:
LLMRec: Large Language Models with Graph Augmentation for Recommendation. CoRR abs/2311.00423 (2023) - [i34]Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang:
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks. CoRR abs/2311.04245 (2023) - [i33]Jiahao Ji, Wentao Zhang, Jingyuan Wang, Yue He, Chao Huang:
Self-Supervised Deconfounding Against Spatio-Temporal Shifts: Theory and Modeling. CoRR abs/2311.12472 (2023) - [i32]Yuhao Yang, Lianghao Xia, Da Luo, Kangyi Lin, Chao Huang:
Graph Pre-training and Prompt Learning for Recommendation. CoRR abs/2311.16716 (2023) - [i31]Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang:
DiffKG: Knowledge Graph Diffusion Model for Recommendation. CoRR abs/2312.16890 (2023) - 2022
- [j11]Kai Wang, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong:
Heterogeneous graph neural network for attribute completion. Knowl. Based Syst. 251: 109171 (2022) - [j10]Xian Wu, Chao Huang, Pablo Robles-Granda, Nitesh V. Chawla:
Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series. ACM Trans. Intell. Syst. Technol. 13(6): 97:1-97:21 (2022) - [j9]Lianghao Xia, Chao Huang, Yong Xu, Huance Xu, Xiang Li, Weiguo Zhang:
Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems. ACM Trans. Inf. Syst. 40(1): 10:1-10:22 (2022) - [c69]Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang:
Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation. CIKM 2022: 2519-2528 - [c68]Chao Huang, Lianghao Xia, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommendation. CIKM 2022: 5136-5139 - [c67]Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, Roger Zimmermann:
When do contrastive learning signals help spatio-temporal graph forecasting? SIGSPATIAL/GIS 2022: 5:1-5:12 - [c66]Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu, Lei Cao, Chao Huang, Junyu Dong:
Scalable Motif Counting for Large-scale Temporal Graphs. ICDE 2022: 2656-2668 - [c65]Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei:
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction. ICDE 2022: 2984-2996 - [c64]Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong:
Mutual Distillation Learning Network for Trajectory-User Linking. IJCAI 2022: 1973-1979 - [c63]Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla:
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. IJCAI 2022: 3466-3472 - [c62]Lianghao Xia, Chao Huang, Chuxu Zhang:
Self-Supervised Hypergraph Transformer for Recommender Systems. KDD 2022: 2100-2109 - [c61]Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li:
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation. KDD 2022: 2263-2274 - [c60]Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong:
Multiplex Heterogeneous Graph Convolutional Network. KDD 2022: 2377-2387 - [c59]Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang:
Hypergraph Contrastive Collaborative Filtering. SIGIR 2022: 70-79 - [c58]Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li:
Knowledge Graph Contrastive Learning for Recommendation. SIGIR 2022: 1434-1443 - [c57]Chao Huang, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommender System. SIGIR 2022: 3440-3443 - [c56]Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, Dawei Yin:
Contrastive Meta Learning with Behavior Multiplicity for Recommendation. WSDM 2022: 1120-1128 - [i30]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Mengyin Lu, Liefeng Bo:
Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling. CoRR abs/2201.02307 (2022) - [i29]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo, Xiyue Zhang, Tianyi Chen:
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction. CoRR abs/2201.02435 (2022) - [i28]Lianghao Xia, Chao Huang, Yong Xu, Huance Xu, Xiang Li, Weiguo Zhang:
Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems. CoRR abs/2201.03158 (2022) - [i27]Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, Dawei Yin:
Contrastive Meta Learning with Behavior Multiplicity for Recommendation. CoRR abs/2202.08523 (2022) - [i26]Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei:
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction. CoRR abs/2204.08587 (2022) - [i25]Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu, Lei Cao, Chao Huang, Junyu Dong:
Scalable Motif Counting for Large-scale Temporal Graphs. CoRR abs/2204.09236 (2022) - [i24]Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy Xiangji Huang:
Hypergraph Contrastive Collaborative Filtering. CoRR abs/2204.12200 (2022) - [i23]Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li:
Knowledge Graph Contrastive Learning for Recommendation. CoRR abs/2205.00976 (2022) - [i22]Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong:
Mutual Distillation Learning Network for Trajectory-User Linking. CoRR abs/2205.03773 (2022) - [i21]Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla:
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. CoRR abs/2205.14005 (2022) - [i20]Lianghao Xia, Chao Huang, Yong Xu, Jian Pei:
Multi-Behavior Sequential Recommendation with Temporal Graph Transformer. CoRR abs/2206.02687 (2022) - [i19]Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li:
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation. CoRR abs/2207.05584 (2022) - [i18]Lianghao Xia, Chao Huang, Chuxu Zhang:
Self-Supervised Hypergraph Transformer for Recommender Systems. CoRR abs/2207.14338 (2022) - [i17]Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong:
Multiplex Heterogeneous Graph Convolutional Network. CoRR abs/2208.06129 (2022) - [i16]Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang:
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning. CoRR abs/2210.00162 (2022) - [i15]Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi:
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning. CoRR abs/2211.08415 (2022) - [i14]Jiahao Ji, Jingyuan Wang, Chao Huang, Junjie Wu, Boren Xu, Zhenhe Wu, Junbo Zhang, Yu Zheng:
Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction. CoRR abs/2212.04475 (2022) - 2021
- [j8]Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla:
Inductive Contextual Relation Learning for Personalization. ACM Trans. Inf. Syst. 39(3): 35:1-35:22 (2021) - [c55]Chao Huang, Huance Xu, Yong Xu, Peng Dai, Lianghao Xia, Mengyin Lu, Liefeng Bo, Hao Xing, Xiaoping Lai, Yanfang Ye:
Knowledge-aware Coupled Graph Neural Network for Social Recommendation. AAAI 2021: 4115-4122 - [c54]Chao Huang, Jiahui Chen, Lianghao Xia, Yong Xu, Peng Dai, Yanqing Chen, Liefeng Bo, Jiashu Zhao, Jimmy Xiangji Huang:
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation. AAAI 2021: 4123-4130 - [c53]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Xiyue Zhang, Hongsheng Yang, Jian Pei, Liefeng Bo:
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation. AAAI 2021: 4486-4493 - [c52]Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng:
Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network. AAAI 2021: 15008-15015 - [c51]Xiaoling Long, Chao Huang, Yong Xu, Huance Xu, Peng Dai, Lianghao Xia, Liefeng Bo:
Social Recommendation with Self-Supervised Metagraph Informax Network. CIKM 2021: 1160-1169 - [c50]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Mengyin Lu, Liefeng Bo:
Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling. ICDE 2021: 1931-1936 - [c49]Chao Huang, Jiashu Zhao, Dawei Yin:
Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks. ICDE 2021: 2488-2498 - [c48]Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, Junyu Dong:
Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference. ICDM 2021: 1042-1047 - [c47]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo, Xiyue Zhang, Tianyi Chen:
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning. IJCAI 2021: 1631-1637 - [c46]Lianghao Xia, Yong Xu, Chao Huang, Peng Dai, Liefeng Bo:
Graph Meta Network for Multi-Behavior Recommendation. SIGIR 2021: 757-766 - [c45]Zhijun Liu, Chao Huang, Yanwei Yu, Junyu Dong:
Motif-Preserving Dynamic Attributed Network Embedding. WWW 2021: 1629-1638 - [i13]Xiaoling Long, Chao Huang, Yong Xu, Huance Xu, Peng Dai, Lianghao Xia, Liefeng Bo:
Social Recommendation with Self-Supervised Metagraph Informax Network. CoRR abs/2110.03958 (2021) - [i12]Lianghao Xia, Yong Xu, Chao Huang, Peng Dai, Liefeng Bo:
Graph Meta Network for Multi-Behavior Recommendation. CoRR abs/2110.03969 (2021) - [i11]Chao Huang, Huance Xu, Yong Xu, Peng Dai, Lianghao Xia, Mengyin Lu, Liefeng Bo, Hao Xing, Xiaoping Lai, Yanfang Ye:
Knowledge-aware Coupled Graph Neural Network for Social Recommendation. CoRR abs/2110.03987 (2021) - [i10]Chao Huang, Jiahui Chen, Lianghao Xia, Yong Xu, Peng Dai, Yanqing Chen, Liefeng Bo, Jiashu Zhao, Jimmy Xiangji Huang:
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation. CoRR abs/2110.03996 (2021) - [i9]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Xiyue Zhang, Hongsheng Yang, Jian Pei, Liefeng Bo:
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation. CoRR abs/2110.04000 (2021) - [i8]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Bo Zhang, Liefeng Bo:
Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network. CoRR abs/2110.04002 (2021) - [i7]Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng:
Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network. CoRR abs/2110.04038 (2021) - [i6]Huance Xu, Chao Huang, Yong Xu, Lianghao Xia, Hao Xing, Dawei Yin:
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks. CoRR abs/2110.04039 (2021) - 2020
- [j7]Chao Huang, Dong Wang, Jun Tao, Brian Mann:
On Physical-Social-Aware Localness Inference by Exploring Big Data from Location-Based Services. IEEE Trans. Big Data 6(4): 679-690 (2020) - [j6]Chao Huang, Dong Wang, Nitesh V. Chawla:
Scalable Uncertainty-Aware Truth Discovery in Big Data Social Sensing Applications for Cyber-Physical Systems. IEEE Trans. Big Data 6(4): 702-713 (2020) - [c44]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. AAAI 2020: 3041-3048 - [c43]Zhijun Liu, Chao Huang, Yanwei Yu, Baode Fan, Junyu Dong:
Fast Attributed Multiplex Heterogeneous Network Embedding. CIKM 2020: 995-1004 - [c42]Zhijun Liu, Chao Huang, Yanwei Yu, Peng Song, Baode Fan, Junyu Dong:
Dynamic Representation Learning for Large-Scale Attributed Networks. CIKM 2020: 1005-1014 - [c41]Xian Wu, Stephen M. Mattingly, Shayan Mirjafari, Chao Huang, Nitesh V. Chawla:
Personalized Imputation on Wearable-Sensory Time Series via Knowledge Transfer. CIKM 2020: 1625-1634 - [c40]Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia:
Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting. CIKM 2020: 1853-1862 - [c39]Yong Xu, Jiahui Chen, Chao Huang, Bo Zhang, Hao Xing, Peng Dai, Liefeng Bo:
Joint Modeling of Local and Global Behavior Dynamics for Session-Based Recommendation. ECAI 2020: 545-552 - [c38]Huance Xu, Chao Huang, Yong Xu, Lianghao Xia, Hao Xing, Dawei Yin:
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks. ICDM 2020: 701-710 - [c37]Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo:
Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction. IJCAI 2020: 4359-4365 - [c36]Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Bo Zhang, Liefeng Bo:
Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network. SIGIR 2020: 2397-2406 - [c35]Xian Wu, Chao Huang, Chuxu Zhang, Nitesh V. Chawla:
Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting. WWW 2020: 2320-2330 - [i5]Xian Wu, Chao Huang, Pablo Robles-Granda, Nitesh V. Chawla:
Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series. CoRR abs/2002.03595 (2020)
2010 – 2019
- 2019
- [c34]Chao Huang, Baoxu Shi, Xuchao Zhang, Xian Wu, Nitesh V. Chawla:
Similarity-Aware Network Embedding with Self-Paced Learning. CIKM 2019: 2113-2116 - [c33]Chao Huang, Xian Wu, Xuchao Zhang, Suwen Lin, Nitesh V. Chawla:
Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity. CIKM 2019: 2141-2144 - [c32]Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo:
Deep Dynamic Fusion Network for Traffic Accident Forecasting. CIKM 2019: 2673-2681 - [c31]Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla:
Heterogeneous Graph Neural Network. KDD 2019: 793-803 - [c30]Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla:
Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. KDD 2019: 2613-2622 - [c29]Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh V. Chawla:
Neural Tensor Factorization for Temporal Interaction Learning. WSDM 2019: 537-545 - [c28]Chao Huang, Chuxu Zhang, Jiashu Zhao, Xian Wu, Nitesh V. Chawla, Dawei Yin:
MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting. WWW 2019: 717-728 - [i4]Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai, Liefeng Bo, Jiawei Zhang:
Heterogeneous Deep Graph Infomax. CoRR abs/1911.08538 (2019) - [i3]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. CoRR abs/1911.11298 (2019) - 2018
- [j5]Dong Wang, Nathan Vance, Chao Huang:
Who to select: Identifying critical sources in social sensing. Knowl. Based Syst. 145: 98-108 (2018) - [c27]Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Louis Faust, Nitesh V. Chawla:
RESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data. CIKM 2018: 1073-1082 - [c26]Chao Huang, Junbo Zhang, Yu Zheng, Nitesh V. Chawla:
DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction. CIKM 2018: 1423-1432 - [c25]Dong Wang, Daniel Zhang, Chao Huang:
Towards Reliable Hypothesis Validation in Social Sensing Applications. SECON 2018: 64-72 - [c24]Chuxu Zhang, Chao Huang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla:
Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification. WWW 2018: 709-718 - [i2]Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh V. Chawla:
Neural Tensor Factorization. CoRR abs/1802.04416 (2018) - 2017
- [j4]Chao Huang, Dong Wang:
Exploring Scalability and Time-Sensitiveness in Reliable Social Sensing With Accuracy Assessment. IEEE Access 5: 14405-14418 (2017) - [j3]Chao Huang, Dong Wang, Brian Mann:
Towards social-aware interesting place finding in social sensing applications. Knowl. Based Syst. 123: 31-40 (2017) - [j2]Chao Huang, Dong Wang, Shenglong Zhu, Brian Mann:
Toward local family relationship discovery in location-based social network. Soc. Netw. Anal. Min. 7(1): 27:1-27:21 (2017) - [j1]Chao Huang, Dong Wang, Jun Tao:
An Unsupervised Approach to Inferring the Localness of People Using Incomplete Geotemporal Online Check-In Data. ACM Trans. Intell. Syst. Technol. 8(6): 80:1-80:18 (2017) - [c23]Chao Huang, Dong Wang, Shenglong Zhu:
Towards Diversified Local Users Identification Using Location Based Social Networks. ASONAM 2017: 115-118 - [c22]Xian Wu, Yuxiao Dong, Jun Tao, Chao Huang, Nitesh V. Chawla:
Reliable fake review detection via modeling temporal and behavioral patterns. IEEE BigData 2017: 494-499 - [c21]Chao Huang, Dong Wang:
Critical Source Selection in Social Sensing Applications. DCOSS 2017: 53-60 - [c20]Daniel Yue Zhang, Chao Zheng, Dong Wang, Douglas Thain, Xin Mu, Greg Madey, Chao Huang:
Towards Scalable and Dynamic Social Sensing Using A Distributed Computing Framework. ICDCS 2017: 966-976 - [c19]Chao Huang, Dong Wang, Shenglong Zhu:
Where are you from: Home location profiling of crowd sensors from noisy and sparse crowdsourcing data. INFOCOM 2017: 1-9 - [c18]Xian Wu, Yuxiao Dong, Chao Huang, Jian Xu, Dong Wang, Nitesh V. Chawla:
UAPD: Predicting Urban Anomalies from Spatial-Temporal Data. ECML/PKDD (2) 2017: 622-638 - [i1]Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla:
Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline. CoRR abs/1706.01513 (2017) - 2016
- [c17]Chao Huang, Dong Wang:
Exploiting spatial-temporal-social constraints for localness inference using online social media. ASONAM 2016: 287-294 - [c16]Chao Huang, Dong Wang, Shenglong Zhu, Daniel Yue Zhang:
Towards unsupervised home location inference from online social media. IEEE BigData 2016: 676-685 - [c15]Daniel Yue Zhang, Rungang Han, Dong Wang, Chao Huang:
On robust truth discovery in sparse social media sensing. IEEE BigData 2016: 1076-1081 - [c14]Chao Huang, Xian Wu, Dong Wang:
Crowdsourcing-based Urban Anomaly Prediction System for Smart Cities. CIKM 2016: 1969-1972 - [c13]Chao Huang, Dong Wang:
Unsupervised Interesting Places Discovery in Location-Based Social Sensing. DCOSS 2016: 67-74 - [c12]Dong Wang, Jermaine Marshall, Chao Huang:
Theme-Relevant Truth Discovery on Twitter: An Estimation Theoretic Approach. ICWSM 2016: 408-416 - [c11]Chao Huang, Jermaine Marshall, Dong Wang, Mianxiong Dong:
Towards Reliable Social Sensing in Cyber-Physical-Social Systems. IPDPS Workshops 2016: 1796-1802 - [c10]Chao Huang, Dong Wang:
Topic-Aware Social Sensing with Arbitrary Source Dependency Graphs. IPSN 2016: 7:1-7:12 - 2015
- [c9]Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla:
Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline. BIRS-IMLKE 2015: 150-169 - [c8]Chao Huang, Dong Wang:
Link weight based truth discovery in social sensing. IPSN 2015: 326-327 - [c7]Chao Huang, Dong Wang, Nitesh V. Chawla:
Towards Time-Sensitive Truth Discovery in Social Sensing Applications. MASS 2015: 154-162 - [c6]Chao Huang, Dong Wang:
Time-Aware Truth Discovery in Social Sensing. MASS 2015: 479-480 - [c5]Chao Huang, Dong Wang, Nitesh V. Chawla:
On spatial-temporal truth finding in social sensing. SECON 2015: 151-153 - [c4]Chao Huang, Dong Wang:
Demo paper: A confidence-aware truth estimation tool for social sensing applications. SECON 2015: 187-189 - [c3]Dong Wang, Chao Huang:
Confidence-aware truth estimation in social sensing applications. SECON 2015: 336-344 - [c2]Chao Huang, Dong Wang:
On Interesting Place Finding in Social Sensing: An Emerging Smart City Application Paradigm. SmartCity 2015: 13-20 - [c1]Chao Huang, Dong Wang:
Spatial-Temporal Aware Truth Finding in Big Data Social Sensing Applications. TrustCom/BigDataSE/ISPA (2) 2015: 72-79
Coauthor Index
[j16] [c106] [c104] [c103] [c102] [c99] [c98] [c97] [i75] [i73] [i72] [i71] [i69] [i68] [i66] [i65] [i64] [i62] [j12] [c94] [c93] [c92] [c90] [c89] [c87] [c86] [c84] [c82] [c80] [c79] [c78] [c77] [c76] [c75] [c73] [c72] [c71] [c70] [i60] [i59] [i58] [i56] [i55] [i54] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i44] [i43] [i42] [i41] [i40] [i38] [i37] [i36] [i34] [i32] [i31] [j9] [c68] [c65] [c62] [c61] [c59] [c58] [c56] [i30] [i29] [i28] [i27] [i26] [i24] [i23] [i20] [i19] [i18] [c55] [c54] [c53] [c52] [c51] [c50] [c47] [c46] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [c40] [c38] [c36]
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