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Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Lei Shen, Zihan Wang, Andi Wang, Yang Li, Teng Su, Zhilin Yang, and Jie Tang. CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Xiao Liu, Hanyu Lai, Yu Hao, Yifan Xu, Aohan Zeng, Zhengxiao Du, Peng Zhang, Yuxiao Dong, and Jie Tang. WebGLM: Towards An Efficient Web-enhanced Question Answering System with Human Preference. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Jing Zhang, Xiaokang Zhang, Daniel Zhang-Li, Jifan Yu, Zijun Yao, Zeyao Ma, Yiqi Xu, Haohua Wang, Xiaohan Zhang, Nianyi Lin, Sunrui Lu, Jie Tang, and Juanzi Li. GLM-Dialog: Noise-tolerant Pre-Training for Knowledge-grounded Dialogue Generation. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Zhitao Ying, Yukuo Cen, Yangliao Geng, and Jie Tang. BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, and Jie Tang. WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, XiaoYan Li, Yuxiao Dong, and Jie Tang. Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
Yuyang Xie, Yuxiao Dong, Jiezhong Qiu, Wenjian Yu, Xu Feng, and Jie Tang. SketchNE: Embedding Billion-Scale Networks Accurately in One Hour. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, and Jie Tang. GLM-130B: An Open Bilingual Pre-trained Model. In Proceedings of the 11th International Conference on Learning Representations (ICLR'23). [PDF] [*Code&Model*] [*Blog*] [*Demo*] [*ChatGLM*]
Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang. CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers. In Proceedings of the 11th International Conference on Learning Representations (ICLR'23). [PDF] [Poster] [*Code&Model*] [*Demo*]
Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, and Jie Tang. CogDL: A Comprehensive Library for Graph Deep Learning. In Proceedings of the Web Conference 2023 (WWW'23). [PDF] [*Code&Data*]
Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, and Jie Tang. GraphMAE2: A Decoding-enhanced Masked Self-supervised Graph Learner. In Proceedings of the Web Conference 2023 (WWW'23) (accepted). [PDF] [*Code&Data*]
Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, and Jie Tang. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation. In Proceedings of the Web Conference 2023 (WWW'23) (accepted). [PDF]
Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, and Chi Wang. Towards Lightweight and Automated Representation Learning System for Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Linking Entities across Large-Scale Heterogeneous Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
Zhenyu Hou, Yukuo Cen, Ziding Liu, Dongxue Wu, Baoyan Wang, Xuanhe Li, Lei Hong, and Jie Tang. MTDiag: An Effective Multi-Task Framework for Automatic Diagnosis. In Proceedings of the 37rd AAAI Conference on Artificial Intelligence (AAAI'23). [PDF]
Ming Ding, Wendi Zheng, Wenyi Hong, and Jie Tang. CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. In Proceedings of the Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS'22). [*Code&Data&Model*] [*Demo*]
Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, and Jie Tang. GraphMAE: Self-Supervised Masked Graph Autoencoders. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, and Jie Tang. Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
Xiao Liu, Da Yin, Jingnan Zheng, Xingjian Zhang, Peng Zhang, Hongxia Yang, Yuxiao Dong, and Jie Tang. OAG-BERT: Towards a Unified Backbone Language Model for Academic Knowledge Services. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
Jifan Yu, Xiaohan Zhang, Yifan Xu, Xuanyu Lei, Xinyu Guan, Jing Zhang, Lei Hou, Juanzi Li, and Jie Tang. XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Demo*]
Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, and Alvin Cheung. GACT: Activation Compressed Training for Generic Network Architectures. In Proceedings of the 39st International Conference on Machine Learning (ICML'22). [PDF]
Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, and Jie Tang. Rethinking the Setting of Semi-supervised Learning on Graphs. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22). [PDF] [*Code&Data*]
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. GLM: General Language Model Pretraining with Autoregressive Blank Infilling. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
Xiao Liu, Kaixuan Ji, Yicheng Fu, Weng Lam Tam, Zhengxiao Du, Zhilin Yang, and Jie Tang. P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, and Zhilin Yang. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*] [LeaderBoard]
Jing Zhou, Yanan Zheng, Jie Tang, Jian Li, and Zhilin Yang. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
Jing Zhang, Xiaokang Zhang, Jifan Yu, Jian Tang, Jie Tang, Cuiping Li, and Hong Chen. Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, and Dawn Song. DeepStruct: Pre-Training of Language Models for Structure Prediction. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (Findings of ACL'22).
Bo Chen, Jing Zhang, Xiaokang Zhang, Yuxiao Dong, Jian Song, Peng Zhang, Kaibo Xu, Evgeny Kharlamov, and Jie Tang. GCCAD: Graph Contrastive Learning for Anomaly Detection. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2022 (accepted).
Zhen Yang, Ming Ding, Xu Zou, Jie Tang, Bin Xu, Chang Zhou, and Hongxia Yang. Region or Global? A Principle for Negative Sampling in Graph-based Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2022 (accepted). [PDF] [*Code&Data*]
Wenzheng Feng, Yuxiao Dong, Huang Tinglin, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, and Jie Tang. GRAND+: Scalable Graph Random Neural Networks. In Proceedings of the Web Conference 2022 (WWW'22) (accepted). [PDF] [*Code&Data*]
Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, and Jie Tang. SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs. In Proceedings of the Web Conference 2022 (WWW'22) (accepted). [PDF] [*Code&Data*] (Best Paper Candidate)
Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, and Jie Tang. STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation. In Proceedings of the Web Conference 2022 (WWW'22). [PDF] [*Code&Data*]
Zixuan Ma, Jiaao He, Jiezhong Qiu, Huanqi Cao, Yuanwei Wang, Zhenbo Sun, Liyan Zheng, Haojie Wang, Shizhi Tang, Tianyu Zheng, Junyang Lin, Guanyu Feng, Zeqiang Huang, Jie Gao, Aohan Zeng, JianWei Zhang, Runxin Zhong, Tianhui Shi, Sha Liu, Weimin Zheng, Jie Tang, Hongxia Yang, Xin Liu, Jidong Zhai, and Wenguang Chen. BAGUALU: Targeting Brain Scale Pretrained Models with over 37 Million Cores. In Proceedings of the 27th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP'22). [PDF]
Bo Chen, Jing Zhang, Xiaokang Zhang, Xiaobin Tang, Lingfan Cai, Hong Chen, Cuiping Li, Peng Zhang, and Jie Tang. CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking. In Proceedings of the 36rd AAAI Conference on Artificial Intelligence (AAAI'22). [PDF] [*Code&Data*]
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, and Jie Tang. CogView: Mastering Text-to-Image Generation via Transformers. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF] [*Code&Data&Model*] [*Demo*]
Jialin Zhao, Yuxiao Dong, Ming Ding, Evgeny Kharlamov, and Jie Tang. Adaptive Diffusion in Graph Neural Networks. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF] [*Code&Data*]
Yi Ma, Xiaotian Hao, Jianye HAO, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Zhaopeng Meng, and Jie Tang. A Reinforcement Learning Based Bi-level Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF]
Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, and Hongxia Yang. UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF]
Qinkai Zheng, Xu Zou, Yuxiao Dong, Yukuo Cen, Da Yin, Jiarong Xu, Yang Yang, and Jie Tang. Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). (NeurIPS 2021 Datasets and Benchmarks) [PDF] [*Code&Data*]
Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, and Philip S. Yu. Hierarchical Representation Learning for Attributed Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, and Jie Tang. Automated Unsupervised Graph Representation Learning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, and Jie Tang. CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
Jie Gong, Xiao Liu, and Jie Tang. How Monetary Incentives Improve Outcomes in MOOCs: Evidence from a Field Experiment. Journal of Economic Behavior and Organization (JEBO), 2021 (accepted). [PDF]
Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. Self-supervised Learning: Generative or Contrastive. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Arxiv] [*Slides*]
Da Yin, Weng Lam Tam, Ming Ding, and Jie Tang. MRT: Tracing the Evolution of Scientific Publications. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Slides_pptx] [Slides_pdf] [*System*]
Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. Controllable Generation from Pre-trained Language Models via Inverse Prompting. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code&Data&Model*] [*Demo*]
Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, and Jie Tang. TDGIA: Effective Injection Attacks on Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jian-guo Jiang, Yuxiao Dong, and Jie Tang. Are we really making much progress? Revisiting, benchmarking and refining the Heterogeneous Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [Slides_pdf] [*Code&Data*] [Leaderboard]
Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, and Jie Tang. MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code*]
Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, and Hongxia Yang. M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
Yuxuan Shi, Gong Cheng, Trung-Kien Tran, Jie Tang, and Evgeny Kharlamov. Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21). [PDF] [*Code*]
Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang. LightNE: A Lightweight Graph Processing System for Network Embedding. In Proceedings of the 2021 ACM SIGMOD international conference on Management of data (SIGMOD'21), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*]
Xiao Liu, Li Mian, Yuxiao Dong, Fanjin Zhang, Jing Zhang, Jie Tang, Peng Zhang, Jibing Gong, and Kuansan Wang. OAG_know: Self-supervised Learning for Linking Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [*Data*] [*Code*]
Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, and Jun Zhu. Pre-Trained Models: Past, Present and Future. AI Open Journal, 2021. [PDF]
Xueyi Liu and Jie Tang. Network Representation Learning: A Macro and Micro Outlook. AI Open Journal, 2021. [PDF] [Slides]
Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, and Philip S. Yu. Understanding WeChat User Preferences and “Wow” Diffusion. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*] [*Data*]
Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, and Jie Tang. Graph Random Neural Networks for Semi-Supervised Learning on Graphs. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [Appendix] [*Code*]
Ming Ding, Chang Zhou, Hongxia Yang, and Jie Tang. CogLTX: Applying BERT to Long Texts. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [*Code*] [*Data*]
Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, and Jie Tang. A Matrix Chernoff Bound for Markov Chains and its Application to Co-occurrence Matrices. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [Slides_ppt] [Slides_pdf]
Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, and Jie Tang. Modelling High-Order Social Relations for Item Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
Bo Chen, Jing Zhang, Jie Tang, Lingfan Cai, Zhaoyu Wang, Shu Zhao, Hong Chen, and Cuiping Li. CONNA: Addressing Name Disambiguation on The Fly. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, and Jie Tang. Understanding Negative Sampling in Graph Representation Learning. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, and Jie Tang. Controllable Multi-Interest Framework for Recommendation. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [*data & code*]
Jibing Gong, Shen Wang, Jinlong Wang, Hao Peng, Wenzheng Feng, Dan Wang, Yi Zhao, Huanhuan Li, Jie Tang, and Philip Yu. Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. In Proceedings of the 43th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'20). [PDF]
Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun and Jie Tang. Heterogeneous Network Representation Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20). [PDF] [Slides_PPT] [Slides_PDF] [Poster]
Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, wenzheng feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu and Jie Tang. MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. In Proceedings of the 58th Annual Meeting of the Association of Computational Linguistics (ACL'20). [PDF] [*data & code*]
Si Zhang, Hanghang Tong, Jie Tang, Jiejun Xu, and Wei Fan. Incomplete Network Alignment: Problem Definitions and Fast Solutions. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, accepted. [PDF]
Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [*data & code*]
Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, and Zhiyuan Liu. Course Concept Expansion in MOOCs with External Knowledge and Interactive Game. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [data & code]
Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data] [code] [code]
Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang and Dan Shen. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Representation Learning for Attributed Multiplex Heterogeneous Network. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Towards Knowledge-Based Personalized Product Description Generation in E-commerce. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou and Jie Tang. Sequential Scenario-Specific Meta Learner for Online Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, and Jie Tang. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. In Proceedings of the Web Conference 2019 (WWW'19) (accepted). [PDF] [*data & code*] (Best Paper Candidate)
Yu Han, Jie Tang, and Qian Chen. Network Embedding under Partial Monitoring for Evolving Networks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [Slides_PPT] [Slides_PDF]
Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, and Ming Ding. ProNE: Fast and Scalable Network Representation Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [*data & code*]
Yifeng Zhao, Xiangwei Wang, Hongxia Yang, Le Song, and Jie Tang. Large Scale Evolving Graphs with Burst Detection. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF]
Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, and Jie Tang. Trust Relationship Prediction in Alibaba E-Commerce Platform. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
Fuli Feng, Xiangnan He, Jie Tang, and Tat-Seng Chua. Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
Zhengxiao Du, Jie Tang, and Yuhui Ding. POLAR++: Active One-shot Personalized Article Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
Wenzheng Feng, Jie Tang, Tracy Xiao Liu, Shuhuai Zhang, and Jian Guan. Understanding Dropouts in MOOCs. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19). [PDF] [data & code]
Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18). [PDF] [Slides] [*code*]
Yi Qi, Qingyun Wu, Hongning Wang, Jie Tang, and Maosong Sun. Bandit Learning with Implicit Feedback. In Proceedings of the Thirty-Second Annual Conference on Neural Information Processing Systems (NeurIPS'18). [PDF]
Yutao Zhang, Fanjin Zhang, Peiran Yao, and Jie Tang. Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [slides] [poster] [data & code] [video]
Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, and Jie Tang. DeepInf: Social Influence Prediction with Deep Learning. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [poster] [data & code] [video]
Yujie Qian, Jie Tang, and Kan Wu. Weakly Learning to Match Experts in Online Community. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
Kan Wu, Jie Tang, and Chenhui Zhang. Where have you been? Inferring career trajectory from academic social network. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Tatseng Chua, Thanassis Tiropanis, and Wendy Hall. Cross-Domain Depression Detection via Harvesting Social Media. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF]
Xiaotao Gu, Hong Yang, Jie Tang, Jing Zhang, Fanjin Zhang, Debing Liu, Wendy Hall, and Xiao Fu. Profiling Web Users Using Big Data. Social Network Analysis and Mining (SNAM), 2018, Volume 8, Issue 1, Pages 24:1-17.. [PDF]
Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. Will Triadic Closure Strengthen Ties in Social Networks? ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12, Issue 3, Article No. 30. [PDF]
Yutao Zhang, Robert Chen, Jie Tang, Jimeng Sun, and Walter Stewart. LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity. In Proceedings of the Twenty-Third ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), pages 1315-1324. [PDF]
Yu Han, Jie Tang, Hao Ye, and Bo Chen. Who to Invite Next? Predicting Invitees of Social Groups. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), pages 921-925. [PDF]
Liangming Pan, Chengjiang Li, Juanzi Li, and Jie Tang. Prerequisite Relation Learning for Concepts in MOOCs. In Proceedings of the 55th Annual Meeting of the Association of Computational Linguistics (ACL'17), pages 1447-1456. [PDF] [Data&Code]
Jie Tang. Computational Models for Social Network Analysis: A Brief Survey. In Proceedings of the Twenty-Sixth World Wide Web Conference (WWW'17), pages 921-925. [PDF] [Slides_PPT]
Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, Juanzi Li, Walter Luyten, and Marie-Francine Moens. Fast and Flexible Top-k Similarity Search on Large Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 2, Article No. 13. [PDF]
Lei Hou, Juanzi Li, Xiao-Li Li, Jie Tang, and Xiaofei Guo. Learning to Align Comments to News Topics. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 1, Article No. 9. [PDF]
Yang Yang, Jie Tang, and Juanzi Li. Learning to Infer Competitive Relationships in Heterogeneous Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12 Issue 1, Article No. 12. [PDF]
Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie, Jie Tang, Ling Feng, and Tat-Seng Chua. Detecting Stress Based on Social Interactions in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2017, Volume 29, Issue 9, Pages 1820-1833. [PDF]
Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, and Yang Yang. User Modeling on Demographic Attributes in Large-Scale Mobile Social Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 35, Issue 4, Article No. 35. [PDF]
Jie Tang and Wendy Hall. Cross-domain Ranking via Latent Space Learning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 2618-2624. [PDF] [Slides_PPT] [Poster]
Jing Zhang, Jie Tang, Yuanyi Zhong, Yuchen Mo, Juanzi Li, Guojie Song, Wendy Hall, and Jimeng Sun. StructInf: Mining Structural Influence from Social Streams. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 73-79. [PDF] [Slides_PPT] [Poster]
Yikang Shen, Wenge Rong, Nan Jiang, Baolin Peng, Jie Tang, Zhang Xiong. Word Embedding Based Correlation Model for Question/Answer Matching. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 3511-3517. [PDF]
Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, and Hanghang Tong. QUINT: On Query-Specific Optimal Networks. In Proceedings of the Twenty-Second ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). [PDF] [Slides_PDF] [Data&Code]
Zhilin Yang, Jie Tang, and William W. Cohen. Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), pages 2287-2293. [PDF] [Slides_PPT] [Slides_PDF] [Thesis (in Chinese)]
Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, and John Hopcroft. The Lifecycle and Cascade of WeChat Social Messaging Groups. In Proceedings of the Twenty-Fifth World Wide Web Conference (WWW'16), pages 311-320. [PDF] [Slides_PPT] [Slides_PDF]
Jie Tang. AMiner: Toward Understanding Big Scholar Data. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM'16), pages 467-467. (Invited Talk) [PDF] [Slides_PPT] [Slides_PDF]
Yang Yang, Jia Jia, Boya Wu, and Jie Tang. Social Role-Aware Emotion Contagion in Image Social Networks. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), pages 65-71. [PDF] [Supplementary materials] [Slides_PPT] [Slides_PDF]
Zhiyuan Wang, Yun Zhou, Jie Tang, and Jar-Der Luo. The Prediction of Venture Capital Co-Investment Based on Structural Balance Theory. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2016, Volume 28, Issue 2, Pages 537-550. [PDF]
Jie Tang, Tiancheng Lou, Jon Kleinberg, and Sen Wu. Transfer Learning to Infer Social Ties across Heterogeneous Networks. ACM Transactions on Information Systems (TOIS), 2016, Volume 34, Issue 2, Article No. 7. [PDF] [Data&Code]
Jie Tang and Juanzi Li. Semantic Mining of Social Networks. Morgan & Claypool Publishers, 2015. [DRAFT]
Lei Shi, Hanghang Tong, Jie Tang, and Chuang Lin. VEGAS: Visual influEnce GrAph Summarization on Citation Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3417-3431. [PDF] [Video Demo]
Hong Huang, Jie Tang, Lu Liu, JarDer Luo, and Xiaoming Fu. Triadic Closure Pattern Analysis and Prediction in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3374-3389. [PDF]
Jing Zhang, Zhanpeng Fang, Wei Chen, and Jie Tang. Diffusion of "Following" Links in Microblogging Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 8, Pages 2093-2106. [PDF]
Jing Zhang, Jie Tang, Juanzi Li, Yang Liu, and Chunxiao Xing. Who Influenced You? Predicting Retweet via Social Influence Locality. ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, Volume 9, Issue 3, Article No. 25. [PDF] [Code&Data]
Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, and Juanzi Li. Panther: Fast Top-k Similarity Search on Large Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1445-1454. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, and Philip Yu. COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1485-1494. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
Yu Han and Jie Tang. Probabilistic Community and Role Model for Social Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 407-416. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, and Bai Wang. CoupledLP: Link Prediction in Coupled Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 199-208. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, and Juanzi Li. Entity Matching across Heterogeneous Sources. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1395-1404. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
Zhanpeng Fang and Jie Tang. Uncovering the Formation of Triadic Closure in Social Networks. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), pages 2062-2068. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
Jie Tang, Zhanpeng Fang, and Jimeng Sun. Incorporating Social Context and Domain Knowledge for Entity Recognition. In Proceedings of the Twenty-Fourth World Wide Web Conference (WWW'15), pages 517-526. [PDF] [Slides_PPT] [Slides_PDF] [Code&Data]
Jie Tang, Chenhui Zhang, Keke Cai, Li Zhang, and Zhong Su. Sampling Representative Users from Large Social Networks. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 304-310. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
Yang Yang, Jie Tang, Cane Wing-Ki Leung, Yizhou Sun, Qicong Chen, Juanzi Li, and Qiang Yang. RAIN: Social Role-Aware Information Diffusion. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 367-373. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, and Nitesh V. Chawla. Inferring User Demographics and Social Strategies in Mobile Social Networks. In Proceedings of the Twentyth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 15-24. [PDF] [Madness] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] [Code Download] (Report by United Nations)
Mi Zhang, Jie Tang, Xuchen Zhang, Xiangyang Xue. Addressing Cold Start in Recommender Systems: A Semi-supervised Co-training Algorithm. In Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'14), pages 73-82. [PDF]
Jing Zhang, Jie Tang, Honglei Zhuang, Cane Wing-Ki Leung, and Juanzi Li. Role-aware Conformity Influence Modeling and Analysis in Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 958-965. [PDF] [Poster] [Data&Code]
Yang Yang, Jia Jia, Shumei Zhang, Boya Wu, Qicong Chen, Juanzi Li, Chunxiao Xing, and Jie Tang. How Do Your Friends on Social Media Disclose Your Emotions? In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 306-312. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
Yang Yang, Walter Luyten, Lu Liu, Marie-Francine Moens, Jie Tang, and Juanzi Li. Forecasting Potential Diabetes Complications. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 313-319. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
Zhigang Wang, Juanzi Li, Shuangjie Li, Mingyang Li, Jie Tang, Kuo Zhang, and Kun Zhang. Cross-lingual Knowledge Validation Based Taxonomy Derivation from Heterogeneous Online Wikis. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 180-186. [PDF] [Poster] [Data]
Zhixin Li, Siqiang Wen, Juanzi Li, Peng Zhang, and Jie Tang. On Modelling Non-linear Topical Dependencies. In Proceedings of the 31st International Conference on Machine Learning (ICML'14), pages 458-466. [PDF]
Hong Huang, Jie Tang, Sen Wu, Lu Liu, and Xiaoming Fu. Mining Triadic Closure Patterns in Social Networks. In Proceedings of the Twenty-Third World Wide Web Conference (WWW'14), pages 499-504. [PDF] [Slides_PPT] [Slides_PDF]
Jie Tang, Sen Wu, and Jimeng Sun. Confluence: Conformity Influence in Large Social Networks. In Proceedings of the Ninteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13), pages 347-355. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] (Oral Presentation)
Yizhou Sun, Jie Tang, Jiawei Han, Cheng Chen, and Manish Gupta. Co-Evolution of Multi-Typed Objects in Dynamic Star Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 12, Pages 2942-2955. [PDF]
Yi Cai, Ho-fung Leung, Qing Li, Hao Han, Jie Tang, Juanzi Li. Typicality-based Collaborative Filtering Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 3, Pages 766-779. [PDF]
Jing Zhang, Biao Liu, Jie Tang, Ting Chen, and Juanzi Li. Social Influence Locality for Modeling Retweeting Behaviors. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2761-2767. [PDF] [Data&Code] [Poster]
Lei Hou, Juanzi Li, Xiaoli Li, Jiangfeng Qu, Xiaofei Guo, Ou Hui, and Jie Tang. What Users Care about: a Framework for Social Content Alignment. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 1401-1407. [PDF] [Data & Readme] [Slides_PDF] [Poster]
Tiancheng Lou and Jie Tang. Mining Structural Hole Spanners Through Information Diffusion in Social Networks. In Proceedings of the Twenty-Second World Wide Web Conference (WWW'13), pages 837-848. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
Tiancheng Lou, Jie Tang, John Hopcroft, Zhanpeng Fang, Xiaowen Ding. Learning to Predict Reciprocity and Triadic Closure in Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2013, Volume 7, Issue 2, Article No. 5. [PDF] [Code&Data] [System]
Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. Cross-domain Collaboration Recommendation. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1285-1293. [PDF] [Slides_PDF Slides_PPT ] [Poster] [Data&Code] [System] [Video] (Full Presentation & Best Poster Award)
Jie Tang, Bo Wang, Yang Yang, Po Hu, Yanting Zhao, Xinyu Yan, Bo Gao, Minlie Huang, Peng Xu, Weichang Li, and Adam K. Usadi. PatentMiner: Topic-driven Patent Analysis and Mining. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1366-1374. [PDF] [Slides] [Poster] [System] [Video]
Rui Yan, Congrui Huang, Jie Tang, Yan Zhang, and Xiaoming Li. To Better Stand on the Shoulder of Giants. In Proceedings of the 2012 ACM/IEEE Joint Conference on Digital Libraries (JCDL'12), pages 51-60. [PDF] (Nominated as Best Student Paper)
Jie Tang, Tiancheng Lou, and Jon Kleinberg. Inferring Social Ties across Heterogeneous Networks. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM'12), pages 743-752. (Plenary presentation) [PDF] [Slides] [Poster] [Data&Code]
Jie Tang, Yuan Zhang, Jimeng Sun, Jinghai Rao, Wenjing Yu, Yiran Chen, and ACM Fong. Quantitative Study of Individual Emotional States in Social Networks. IEEE Transactions on Affective Computing (TAC), 2012, Volume 3, Issue 2, Pages 132-144. [PDF] (Selected as the Spotlight Paper. Available here)
Jie Tang, A.C.M. Fong, Bo Wang, and Jing Zhang. A Unified Probabilistic Framework for Name Disambiguation in Digital Library. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2012, Volume 24, Issue 6, Pages 975-987. [PDF] [Data]
Bing He, Jie Tang, Ying Ding, Huijun Wang, Yuyin Sun, Jae Hong Shin, Bin Chen, Ganesh Moorthy, Judy Qiu, Pankaj Desai, David J. Wild. Mining relational paths in integrated biomedical data. PLOS ONE, 2011, 6(12). [PDF]
Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, and Zhong Su. Topic Level Expertise Search over Heterogeneous Networks. Machine Learning Journal, 2011, Volume 82, Issue 2, Pages 211-237. [PDF] [URL]
Jie Tang, Limin Yao, Duo Zhang, and Jing Zhang. A Combination Approach to Web User Profiling. ACM Transactions on Knowledge Discovery from Data (TKDD), 2010, Volume 5, Issue 1, Article 2. [PDF]
Wenbin Tang, Honglei Zhuang, and Jie Tang. Learning to Infer Social Ties in Large Networks. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11), pages381-397. [PDF] [Slides] [Data&Code] (Best Student Paper Runner-up)
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, and Juanzi Li. Social Context Summarization. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'11), pages 255-264. [PDF]
Chenhao Tan, Lillian Lee, Jie Tang, Long Jiang, Ming Zhou, and Ping Li. User-level sentiment analysis incorporating social networks. In Proceedings of the Seventeenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pages 1397-1405. [PDF] [Poster] (Top 4 cited papers among all KDD 2011's papers, More...)
Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, and Fengjiao Wang. Social Action Tracking via Noise Tolerant Time-varying Factor Graphs. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 1049-1058. [PDF] [Slides] [Data&Code]
Chi Wang, Jiawei Han, Yuntao Jia, Jie Tang, Duo Zhang, Yintao Yu, and Jingyi Guo. Mining Advisor-Advisee Relationships from Research Publication Networks. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 203-212. [PDF] [Slides] [System] [Data&Code]
Jie Tang, Jimeng Sun, Chi Wang, and Zi Yang. Social Influence Analysis in Large-scale Networks. In Proceedings of the Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09), pages 807-816. [PDF] [Slides] [Data] [Code] (Top 4 cited papers among all papers published at KDD 2009-2013's, More...)
Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08), pages990-998. [PDF] [Slides] [System] [API] [Citation Data] [DBLP Citation Data] [Author-Conference-Topic (ACT) Model (source code)] [More Data] (SIGKDD Test-of-Time Award, the 2nd most-cited paper among all KDD 2008's papers, More...)
Jie Tang, Hang Li, Yunbo Cao, and Zhaohui Tang. Email Data Cleaning. In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'05), pages 489-499. [PDF] [Slides]
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