Yaqing Wang, Subhabrata Mukherjee, Xiaodong Liu, Jing Gao, Ahmed Hassan Awadallah, Jianfeng Gao. LiST: Lite Prompted Self-training Makes Efficient Few-shot Learners . Findings of the Association for Computational Linguistics: NAACL 2022. Seattle, WA, United States. July, 2022

Haoyu Wang, Handong Zhao, Yaqing Wang, Tong Yu, Jiuxiang Gu, and Jing Gao. FedKC: Federated Knowledge Composition for Multilingual Natural Language Understanding. The Web Conference, April 2022.

Tianqi Wang, Fenglong Ma, Tang Tang, Longfei Zhang and Jing Gao. Textbook Enhanced Student Learning Outcome Prediction. Proceedings of the SIAM International Conference on Data Mining, Alexandria, Virginia, U.S, April, 2022.

Hengtong Zhang, Tianhang Zheng, Yaliang Li, Jing Gao, Lu Su, Bo Li. Profanity-Avoiding Training Framework for Seq2seq Models with Certified Robustness. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Online and in the Barceló Bávaro Convention Centre, Punta Cana, Dominican Republic. November 2021.

Haoyu Wang, Fenglong Ma, Yaqing Wang, Jing Gao. Knowledge-Guided Paraphrase Identification. Findings of the Association for Computational Linguistics: EMNLP 2021, Online and in the Barceló Bávaro Convention Centre, Punta Cana, Dominican Republic. November 2021.

Yaqing Wang, Haoda Chu, Chao Zhang and Jing Gao. Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework. Findings of the Association for Computational Linguistics: EMNLP 2021, Online and in the Barceló Bávaro Convention Centre, Punta Cana, Dominican Republic. November 2021.

Haoyu Wang, Xuan Wang, Yaqing Wang, Guangxu Xun, Kishlay Jha, Jing Gao, Nan Yang, Wayne Xin Zhao. InterHG: an Interpretable and Accurate Model for Hypothesis Generation. IEEE International Conference on Bioinformatics and Biomedicine, online, Dec. 2021.

Haoyu Wang, Yaqing Wang, Defu Lian and Jing Gao. A Lightweight Knowledge Graph Embedding Framework for Efficient Inference and Storage. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, Online, November 2021.

Liuyi Yao, Yaliang Li, Sheng Li, Mengdi Huai, Jing Gao, Aidong Zhang. SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, Online, November 2021.

Rui Li, Fenglong Ma and Jing Gao. Integrating Multimodal Electronic Health Records for Diagnosis Prediction. Proceedings of the AMIA 2021 Annual Symposium, San Diego, CA, United States, October, 2021.

Tianqi Wang, Lei Lin, Jing Gao. Explainable Multi-task Flight Arrival Delay Prediction. IEEE International Intelligent Transportation Systems Conference, Indianapolis, IN, United States, September, 2021.

Hengtong Zhang*, Changxin Tian*, Yaliang Li, Lu Su, Jing Gao, Nan Yang, Wayne Xin Zhao. Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual. August, 2021.

Hengtong Zhang, Jing Gao and Lu Su. Data Poisoning Attacks Against Outcome Interpretations of Predictive Models. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual. August, 2021.

Yaqing Wang, Subhabrata Mukherjee, Haoda Chu, Yuancheng Tu, Ming Wu, Jing Gao and Ahmed Hassan Awadallah. Meta Self-training for Few-shot Neural Sequence Labeling. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual. August, 2021.

Yaqing Wang, Fenglong Ma, Haoyu Wang, Kishlay Jha and Jing Gao. Multi-modal Emergent Fake News Detection via Meta Neural Process Networks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual. August, 2021.

Tianqi Wang, Fenglong Ma, Yaqing Wang, Tang Tang, Longfei Zhang, Jing Gao. Towards Learning Outcome Prediction via Modeling Question Explanations and Student Responses . SIAM International Conference on Data Mining, Virtual. March, 2021.

Haoyu Wang, Hengtong Zhang, Yaqing Wang, Jing Gao. Fair Classification Under Strict Unawareness. SIAM International Conference on Data Mining, Virtual. March, 2021.

Yaqing Wang, Fenglong Ma, Jing Gao. Efficient Knowledge Graph Validation via Cross-Graph Representation Learning. ACM International Conference on Information and Knowledge Management, Virtual, October, 2020.

Haoyu Liu, Fenglong Ma, Yaqing Wang, Shibo He, Jiming Chen, Jing Gao. LP-Explain: Local Pictorial Explanation for Outliers. IEEE International Conference on Data Mining, Virtual, October, 2020.

Yaqing Wang, Yifan Ethan Xu, Xian Li, Xin Luna Dong, Jing Gao. Automatic Validation of Textual Attribute Values in ECommerce Catalog by Learning with Limited Labeled Data. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual, August, 2020.

Fenglong Ma, Yaqing Wang, Jing Gao, Houping Xiao, and Jing Zhou. Rare Disease Prediction by Generating Quality-Assured Electronic Health Records. SIAM International Conference on Data Mining, Virtual, May, 2020.

Hengtong Zhang, Yaliang Li, Bolin Ding, Jing Gao. Practical Data Poisoning Attack against Next-Item Recommendation. The Web Conference, Virtual, April 2020.

Yaqing Wang, Weifeng Yang, Fenglong Ma, Jin Xu, Bin Zhong, Qian Deng, Jing Gao. Weak Supervision for Fake News Detection via Reinforcement Learning. AAAI Conference on Artificial Intelligence, New York, NY, February 2020.

Chen Ye, Hongzhi Wang, Kangjie Zheng, Youkang Kong, Rong Zhu, Jing Gao, Jianzhong Li. Constrained Truth Discovery. IEEE Transactions on Knowledge and Data Engineering, 2020.

Tianqi Wang, Houping Xiao, Fenglong Ma, Jing Gao. IProWA: A Novel Probabilistic Graphical Model for Crowdsourcing Aggregation. IEEE International Conference on Big Data, Los Angeles, CA, December 2019.

Rui Li, Fenglong Ma, Wenjun Jiang, Jing Gao. Online Federated Multitask Learning. IEEE International Conference on Big Data, Los Angeles, CA, December 2019.

Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang. ACE: Adaptively Similarity-preserved Representation Learning for Individual Treatment Effect Estimation. IEEE International Conference on Data Mining, Beijing, China, November 2019.

Chen Ye, Qi Li, Hengtong Zhang, Hongzhi Wang, Jing Gao, Jianzhong Li. AutoRepair: An Automatic Repairing Approach over Multi-Source Data. Knowledge and Information Systems, Vol.61(1), pp.227-257, October 2019.

Fenglong Ma, Shiran Zhong, Jing Gao, Ling Bian. Influenza-Like Symptom Prediction by Analyzing Self-Reported Health Status and Human Mobility Behaviors. ACM Conference on Bioinformatics, Computational Biology and Health Informatics, Niagara Falls, NY, September 2019, 233-242. Acceptance Rate: 42/157 = 27%.

Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Jing Gao, Aidong Zhang. Metric Learning on Healthcare Data with Incomplete Modalities. International Joint Conference on Artificial Intelligence, Macao, China, August 2019, 3534-3540. Acceptance Rate: 850/4752 = 17.89%.

Liuyi Yao, Sheng Li, Yaliang Li, Hongfei Xue, Jing Gao, Aidong Zhang. On the Estimation of Treatment Effect with Text Covariates. International Joint Conference on Artificial Intelligence, Macao, China, August 2019, 4106-4113. Acceptance Rate: 850/4752 = 17.89%.

Hengtong Zhang, Tianhang Zheng, Jing Gao, Chenglin Miao, Lu Su, Yaliang Li, Kui Ren. Data Poisoning Attack against Knowledge Graph Embedding. International Joint Conference on Artificial Intelligence, Macao, China, August 2019, 4853-4859. Acceptance Rate: 850/4752 = 17.89%.

Tianqi Wang, Qi Li, Jing Gao, Xia Jing, Jie Tang. Improving Peer Assessment Accuracy by Incorporating Relative Peer Grades. International Conference on Educational Data Mining, Montreal, Canada, July 2019, 450-455. Acceptance Rate: 64/185 = 34.6%.

Tianqi Wang, Fenglong Ma, Jing Gao. Deep Hierarchical Knowledge Tracing. International Conference on Educational Data Mining, Montreal, Canada, July 2019, 671-674. Acceptance Rate: 64/185 = 34.6%.

Chen Ye, Hongzhi Wang, Tingting Ma, Jing Gao, Hengtong Zhang, Jianzhong Li. Pattern-Finder: Pattern Discovery for Truth Discovery.. Knowledge-Based Systems, Vol.176, pp.97-109, July 2019.

Fenglong Ma, Yaliang Li, Chenwei Zhang, Jing Gao, Nan Du, Wei Fan. MCVAE: Margin based Conditional Variational Autoencoder for Relation Classification and Pattern Generation. The Web Conference, San Francisco, CA, May 2019, 3041-3048. Acceptance Rate: 72/361 = 20%.

Liuyi Yao, Yaliang Li, Yezheng Li, Hengtong Zhang, Mengdi Huai, Jing Gao, Aidong Zhang. DTEC: Distance Transformation Based Early Time Series Classification. SIAM International Conference on Data Mining, Calgary, Canada, May 2019, 486-494.

Houping Xiao, Jing Gao, Qi Li, Fenglong Ma, Yunlong Feng, Aidong Zhang. Towards Confidence Interval Estimation in Truth Discovery. IEEE Transactions on Knowledge and Data Engineering,Vol.31(3), pp.575-588, March 2019.

Chenglin Miao, Wenjun Jiang, Lu Su, Yaliang Li, Suxin Guo, Zhan Qin, Houping Xiao, Jing Gao, Kui Ren. Privacy-Preserving Truth Discovery in Crowd Sensing Systems. ACM Transactions on Sensor Networks, Vol.15(1), 9:1-9:32, February 2019.

Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang. Representation Learning for Treatment Effect Estimation from Observational Data. Advances in Neural Information Processing Systems 31, Montreal, Canada, December 2018, 2638-2648. Acceptance Rate: 1011/4856 = 20.82%.

Fenglong Ma, Yaqing Wang, Houping Xiao, Ye Yuan, Radha Chitta, Jing Zhou, Jing Gao. A General Framework for Diagnosis Prediction via Incorporating Medical Code Descriptions. IEEE International Conference on Bioinformatics and Biomedicine, Madrid, Spain, December 2018. Acceptance Rate: 105/534 = 19.6%.

Yu Cui, Chuishi Meng, Qing He, Jing Gao. Forecasting Current and Next Trip Purpose with Social Media Data and Google Places. Transportation Research Part C: Emerging Technologies, Vol.97, pp.159-174, December 2018.

Houping Xiao, FeiWang, Fenglong Ma, Jing Gao. eOTD: An Efficient Online Tucker Decomposition for Higher Order Tensors. IEEE International Conference on Data Mining, Singapore, November 2018, 1326-1331. Acceptance Rate: 105/948 = 11.08%.

Fenglong Ma, Quanzeng You, Houping Xiao, Radha Chitta, Jing Zhou, Jing Gao. KAME: Knowledge-based Attention Model for Diagnosis Prediction in Healthcare. ACM International Conference on Information and Knowledge Management, Turin, Italy, October 2018, 743-752. Acceptance Rate: 147/862 = 17.05%.

Hengtong Zhang, Fenglong Ma, Yaliang Li, Chao Zhang, Tianqi Wang, Yaqing Wang, Jing Gao, Lu Su. Leveraging the Power of Informative Users for Local Event Detection. IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Barcelona, Spain, August 2018, 429-436. Acceptance Rate: 15%.

Qi Li, Meng Jiang, Xikun Zhang, Meng Qu, Timothy Hanratty, Jing Gao, Jiawei Han. TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, August 2018, 1675-1684. Acceptance Rate: 107/983 = 10.89%.

Yaliang Li, Chenglin Miao, Lu Su, Jing Gao, Qi Li, Bolin Ding, Zhan Qin, Kui Ren. An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, August 2018, 1705-1714. Acceptance Rate: 107/983 = 10.89%.

Fenglong Ma, Jing Gao, Qiuling Suo, Quanzeng You, Jing Zhou and Aidong Zhang. Risk Prediction on Electronic Health Records with Prior Medical Knowledge. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, August 2018, 1910-1919. Acceptance Rate: 107/983 = 10.89%. 

Hengtong Zhang, Yaliang Li, Fenglong Ma, Jing Gao, Lu Su. TextTruth: An Unsupervised Approach to Discover Trustworthy Information from Multi-Sourced Text Data. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, August 2018, 2729-2737. Acceptance Rate: 107/983 = 10.89%.

Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su, Jing Gao. EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, August 2018, 849-857. Acceptance Rate: 112/496 = 22.6%. 

Qiuling Suo, Fenglong Ma, Giovanni Canino, Jing Gao, Aidong Zhang, Agostino Gnasso, Giuseppe Tradigo, Pierangelo Veltri. An Attention-based Recurrent Neural Networks Framework for Health Data Analysis. Proceedings of the 26th Italian Symposium on Advanced Database Systems, Castellaneta Marina, Italy, June 2018.

Liuyi Yao, Lu Su, Qi Li, Yaliang Li, Fenglong Ma, Jing Gao, Aidong Zhang. Online Truth Discovery on Time Series Data. SIAM International Conference on Data Mining, San Diego, CA, May 2018, 162-170. Acceptance Rate: 23.2%.

Mengdi Huai, Chenglin Miao, Qiuling Suo, Yaliang Li, Jing Gao, Aidong Zhang. Uncorrelated Patient Similarity Learning. SIAM Conference on Data Mining, San Diego, CA, May 2018, 270-278. Acceptance Rate: 23.2%.

Chenglin Miao, Qi Li, Lu Su, Mengdi Huai, Wenjun Jiang, Jing Gao. Attack under Disguise: An Intelligent Data Poisoning Attack Mechanism in Crowdsourcing. The Web Conference, Lyon, France, April 2018, 13-22.

Zhenhua Zhang, Qing He, Jing Gao, Ming Ni. A Deep Learning Approach for Detecting Traffic Accidents from Social Media Data. Transportation Research Part C: Emerging Technologies, Vol.86, pp.580-596, January 2018.

Wenjun Jiang, Chenglin Miao, Lu Su, Qi Li, Shaohan Hu, ShiguangWang, Jing Gao, Hengchang Liu, Tarek F. Abdelzaher, Jiawei Han, Xue (Steve) Liu, Yan Gao, Lance M. Kaplan. Towards Quality Aware Information Integration in Distributed Sensing Systems. IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol.29, No.1, pp.198-211, January 2018.

Yaqing Wang, Fenglong Ma, Lu Su, Jing Gao. Discovering Truths from Distributed Data. New Orleans, LA, November 2017, 505-514. Acceptance Rate: 72/778 = 9.25%.

Chuishi Meng, Yu Cui, Qing He, Lu Su, Jing Gao. Travel Purpose Inference with GPS Trajectories, POIs, and Geotagged Social Media Data. IEEE Conference on Big Data, Boston, MA, December 2017, 1319-1324. Acceptance Rate: 87/437 = 20%.

Chuishi Meng, Xiuwen Yi, Lu Su, Jing Gao, Yu Zheng. City-wide Traffic Volume Inference with Loop Detector Data and Taxi Trajectories. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, November 2017, 1:1-1:10. Acceptance Rate: 32/178 = 18%.

Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, Aidong Zhang, Jing Gao. Personalized Disease Prediction Using a CNN-based Similarity Learning Method. IEEE International Conference on Bioinformatics and Biomedicine, Kansas City, MO, November 2017, 811-816.

Qiuling Suo, Fenglong Ma, Giovanni Canino, Jing Gao, Aidong Zhang, Pierangelo Veltri, Agostino Gnasso. A Multi-Task Framework for Monitoring Health Conditions via Attention based Recurrent Neural Networks. AMIA 2017 Annual Symposium, Washington DC, USA, November 2017.

Fenglong Ma, Chuishi Meng, Houping Xiao, Qi Li, Jing Gao, Lu Su, Aidong Zhang. Unsupervised Discovery of Drug Side-Effects from Heterogeneous Data Sources. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, August 2017, 967-976. Acceptance Rate: 131/748 = 17.5%.

Fenglong Ma, Radha Chitta, Jing Zhou, Quanzeng You, Tong Sun, Jing Gao. Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, August 2017, 1903-1911. Acceptance Rate: 85/396 = 21.5%. 

Houping Xiao, Jing Gao, Long Vu, Deepak Turaga. Learning Temporal State of Diabetes Patients via Combining Behavioral and Demographic Data. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, August 2017, 2081-2089. Acceptance Rate: 85/396 = 21.5%.

Guangxu Xun, Yaliang Li, Jing Gao, Aidong Zhang. Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, August 2017, 535-543. Acceptance Rate: 64/748 = 8.6%.

Guangxu Xun, Yaliang Li, Xin Zhao, Jing Gao, Aidong Zhang. A Correlated Topic Model Using Word Embeddings. International Joint Conference on Artificial Intelligence, Melbourne, Australia, August 2017, 4207-4213. Acceptance Rate: 660/2540 = 26%.

Ming Ni, Qing He, Jing Gao. Forecasting the Subway Passenger Flow under Event Occurrences with Social Media. IEEE Transactions on Intelligent Transportation Systems (ITS), Vol.18, No.6, pp.1623-1632, June 2017.

Houping Xiao, Jing Gao, Long Vu, Deepak Turaga. Detecting Malicious Behavior in Computer Networks via Cost-Sensitive and Connectivity Constrained Classification. SIAM International Conference on Data Mining, Houston, TX, April 2017, 117-125. Acceptance Rate: 26%.

Yaliang Li, Nan Du, Chaochun Liu, Yusheng Xie, Wei Fan, Qi Li, Jing Gao, Huan Sun. Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts. ACM International Conference on Web Search and Data Mining, Cambridge, UK, February 2017, 253-261. Acceptance Rate: 80/505 = 16%.

Yaliang Li, Qi Li, Jing Gao, Patrick Lee, Wei Fan, Lu Su, Caifeng He, Cheng He, Fan Yang. A Weighted Crowdsourcing Approach for Network Quality Measurement in Cellular Data Networks. IEEE Transactions on Mobile Computing, Vol.16, No.2, pp.300-313, February 2017.

Guangxu Xun, Vishrawas Gopalakrishnan, Fenglong Ma, Yaliang Li, Jing Gao, Aidong Zhang. Topic Discovery for Short Texts Using Word Embeddings. IEEE International Conference on Data Mining, Barcelona, Spain, December 2016, 1299-1304. Acceptance Rate: 178/904 = 19.6%.

Hengtong Zhang, Qi Li, Fenglong Ma, Houping Xiao, Yaliang Li, Jing Gao, Lu Su. Influence-Aware Truth Discovery. ACM International Conference on Information and Knowledge Management, Indianapolis, IN, October 2016, 851-860. Acceptance Rate: 165/935 = 17.6%.

Chenwei Zhang, Sihong Xie, Yaliang Li, Jing Gao, Wei Fan, Philip S. Yu. Multi-source Hierarchical Prediction Consolidation. ACM International Conference on Information and Knowledge Management, Indianapolis, IN, October 2016, 2251-2256. Acceptance Rate: 270/935 = 28.9%.

Qiuling Suo, Hongfei Xue, Jing Gao, Aidong Zhang. Risk Factor Analysis based on Deep Learning Models. ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, Seattle, WA, October 2016, 394-403.

Yaliang Li, Chaochun Liu, Nan Du, Wei Fan, Qi Li, Jing Gao, Chenwei Zhang, Hao Wu. Extracting Medical Knowledge from Crowdsourced Question Answering Website. IEEE Transactions on Big Data, accepted, September 2016.

Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu. A Truth Discovery Approach with Theoretical Guarantee. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016, 1925-1934. Acceptance Rate: 142/784 = 18.1%. 

Houping Xiao, Jing Gao, Qi Li, Fenglong Ma, Lu Su, Yunlong Feng, Aidong Zhang. Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016, 1935-1944. Acceptance Rate: 142/784 = 18.1%. 

Mengting Wan, Xiangyu Chen, Lance Kaplan, Jiawei Han, Jing Gao, Bo Zhao. From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016, 1885-1894. Acceptance Rate: 142/784 = 18.1%.

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, Jiawei Han. Conflicts to Harmony: A Framework for Resolving Conflicts in Heterogeneous Data by Truth Discovery. IEEE Transactions on Knowledge and Data Engineering, Vol.28, No.8, pp.1986-1999, August 2016.

Christopher Quinn, Ali Pinar, Jing Gao, Lu Su. Sparse Approximations of Directed Information Graphs. IEEE International Symposium on Information Theory, Barcelona, Spain, July 2016, 1735-1739.

Hu Ding, Jing Gao, Jinhui Xu. Finding Global Optimum for Truth Discovery: Entropy Based Geometric Variance. International Symposium on Computational Geometry, Boston, MA, June 2016, 34:1-34:16.

Sihong Xie, Qingbo Hu, Weixiang Shao, Jingyuan Zhang, Jing Gao, Wei Fan, Philip S. Yu. Effective Crowd Expertise Modeling via Cross Domain Sparsity and Uncertainty Reduction. SIAM International Conference on Data Mining, Miami, FL, May 2016.

Qi Li, Fenglong Ma, Jing Gao, Lu Su, Christopher J Quinn. Crowdsourcing High Quality Labels with a Tight Budget. ACM International Conference on Web Search and Data Mining, San Francisco, CA, February 2016, 237-246. Acceptance Rate: 67/368 = 18.2%.

Zhenhua Zhang, Ming Ni, Qing He, Jing Gao, Jizhan Gou, Xiaoling Li. An Exploratory Study on the Correlation between Twitter Concentration and Traffic Surge. Transportation Research Record, in press, 2016.

Zhenhua Zhang, Ming Ni, Qing He, Jing Gao, Jizhan Gou, Xiaoling Li. Identifying On-Site Traffic Accidents Using Both Traffic and Social Media Data. Transportation Research Board Annual Meeting, Washington DC, January 2016.

Ming Ni, Qing He, Jing Gao. Nonrecurrent Subway Passenger Flow Prediction from Social Media Under Event Occurrences. Transportation Research Board Annual Meeting, Washington DC, January 2016.

Yaliang Li, Jing Gao, Chuishi Meng, Qi Li, Lu Su, Bo Zhao, Wei Fan, Jiawei Han. A Survey on Truth Discovery. SIGKDD Explorations, 17(12): 1-16, December 2015.

Nan Du, Xiaowei Jia, Jing Gao, Vishrawas Gopalakrishnan, Aidong Zhang. Tracking Temporal Community Strength in Dynamic Networks. IEEE Transactions on Knowledge and Data Engineering, 27(11): 3125-3137, November 2015.

Chuishi Meng, Wenjun Jiang, Yaliang Li, Jing Gao, Lu Su, Hu Ding, Yun Cheng. Truth Discovery on Crowd Sensing of Correlated Entities. ACM International Conference on Embedded Networked Sensor Systems, Seoul, South Korea, November 2015, 169-182. Acceptance Rate: 27/132 = 20.5%.

Chenglin Miao, Wenjun Jiang, Lu Su, Yaliang Li, Suxin Guo, Zhan Qin, Houping Xiao, Jing Gao, Kui Ren. Truth Discovery on Crowd Sensing of Correlated Entities. ACM International Conference on Embedded Networked Sensor Systems, Seoul, South Korea, November 2015, 183-196. Acceptance Rate: 27/132 = 20.5%.

Xiaoyi Li, Xiaowei Jia, Hui Li, Houping Xiao, Jing Gao, Aidong Zhang. DRN: Bringing Greedy Layered Training into Time Dimension. IEEE International Conference on Data Mining, Atlantic City, NJ, November 2015, 859-864. Acceptance Rate: 18.2%.

Sihong Xie, Qingbo Hu, Jingyuan Zhang, Jing Gao, Wei Fan, Philip S. Yu. Robust Crowd Bias Correction Via Dual Knowledge Transfer from Multiple Overlapping Sources. IEEE International Conference on Big Data, Santa Clara, CA, October 2015, 815-820.

Xian Wu, Wei Fan, Jing Gao, Zi-Ming Feng, Yong Yu. Detecting Marionette Microblog Users for Improved Information Credibility. Journal of Computer Science and Technology, 30(5): 1082-1096, September 2015.

Qi Li, Yaliang Li, Jing Gao, Lu Su, Bo Zhao, Murat Demirbas, Wei Fan, Jiawei Han. A Confidence-Aware Approach for Truth Discovery on Long-Tail Data. International Conference on Very Large Data Bases, Kohala Coast, HI, August 2015, 8(4): 425-436. 

Nan Du, Jing Gao, Liang Ge, Vishrawas Gopalakrishnan, Xiaowei Jia, Kang Li, Aidong Zhang. Significant Edge Detection in Target Network by Exploring Multiple Auxiliary Networks. IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Paris, France, August 2015, 210-217. Acceptance Rate: 49/272 = 18%.

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, Jiawei Han. On the Discovery of Evolving Truth. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 675-684. Acceptance Rate: 159/819 = 19.4%.

Fenglong Ma, Yaliang Li, Qi Li, Minghui Qui, Jing Gao, Shi Zhi, Lu Su, Bo Zhao, Heng Ji, Jiawei Han. FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 745-754. Acceptance Rate: 159/819 = 19.4%. 

Shi Zhi, Bo Zhao, Wenzhu Tong, Jing Gao, Dian Yu, Heng Ji, Jiawei Han. Modeling Truth Existence in Truth Discovery. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 1543-1552. Acceptance Rate: 159/819 = 19.4%. 

Houping Xiao, Jing Gao, Deepak Turaga, Long Vu, Alain Biem. Temporal Multi-View Inconsistency Detection for Network Traffic Analysis. International World Wide Web Conference, Florence, Italy, May 2015, 455-465.

Kang Li, Jing Gao, Suxin Guo, Nan Du, Aidong Zhang. Functional Node Detection on Linked Data. SIAM International Conference on Data Mining, Vancouver, Canada, April 2015, 1-9.

Jialu Liu, Chi Wang, Jing Gao, Quanquan Gu, Charu Aggarwal, Lance Kaplan, Jiawei Han. GIN: A Unified Model for Capturing Dual Heterogeneity in Clustering Networked Data. SIAM International Conference on Data Mining, Vancouver, Canada, April 2015, 388-396.

Houping Xiao, Yaliang Li, Jing Gao, Fei Wang, Liang Ge, Wei Fan, Long Vu, Deepak Turaga. Believe It Today or Tomorrow? Detecting Untrustworthy Information from Dynamic Multi-Source Data. SIAM International Conference on Data Mining, Vancouver, Canada, April 2015, 397-405.

Bowen Dong, Sihong Xie, Jing Gao, Wei Fan, Philip S. Yu. OnlineCM: Real-time Consensus Classification with Missing Values. SIAM International Conference on Data Mining, Vancouver, Canada, April 2015, 685-693.

Lei Lin, Ming Ni, Qing He, Jing Gao, Adel W. Sadek. Modeling the Impacts of Inclement Weather on Freeway Traffic Speed: An Exploratory Study Utilizing Social Media Data. Transportation Research Board Annual Meeting, Washington, DC, January 2015.

Kang Li, Jing Gao, Suxin Guo, Nan Du, Xiaoyi Li, Aidong Zhang. LRBM: A Restricted Boltzmann Machine based Approach for Representation Learning on Linked Data. IEEE International Conference on Data Mining, Shenzhen, China, December 2014. Acceptance Rate: 9.7%.

Lu Su, Qi Li, Shaohan Hu, Shiguang Wang, Jing Gao, Hengchang Liu, Tarek Abdelzaher, Jiawei Han, Xue Liu, Yan Gao, Lance Kaplan. Generalized Decision Aggregation in Distributed Sensing Systems. IEEE Real-Time Systems Symposium, Rome, Italy, December 2014.

Xiaowei Jia, Nan Du, Jing Gao, Aidong Zhang. Analysis on Community Variational Trend in Dynamic Networks. ACM International Conference on Information and Knowledge Management, Shanghai, China, November 2014, 151-160.

Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Han. Outlier Detection for Temporal Data: A Survey. IEEE Transactions on Knowledge and Data Engineering, 26(9): 2250-2267, September 2014.

Sihong Xie, Jing Gao, Wei Fan, Deepak Turaga, Philip S. Yu. Class-Distribution Regularized Consensus Maximization for Alleviating Overfitting in Model Combination. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, August 2014, 303-312. Acceptance Rate: 151/1036 = 14.6%. 

Bahadir Aydin, Yavuz Yilmaz, Yaliang Li, Qi Li, Jing Gao, Murat Demirbas. Crowdsourcing for Multiple-Choice Question Answering. Annual Conference on Innovative Applications of Artificial Intelligence, Quebec City, Canada, July 2014, 2946-2953.

Yaliang Li, Jing Gao, Qi Li, Wei Fan. Ensemble Learning. C. Aggarwal (ed.) Data Classification: Algorithms and Applications, Taylor & Francis, 2014, 483-510.

Qi Li, Yaliang Li, Jing Gao, Bo Zhao, Wei Fan, Jiawei Han. Resolving Conflicts in Heterogeneous Data by Truth Discovery and Source Reliability Estimation. ACM SIGMOD International Conference on Management of Data, Snowbird, UT, June 2014, 1187-1198. 

Xiaoyi Li, Nan Du, Hui Li, Kang Li, Jing Gao, Aidong Zhang. A Deep Learning Approach to Link Prediction in Dynamic Networks. SIAM International Conference on Data Mining, Philadelphia, PA, April 2014, 289-297.

Ke Wu, Andrea Edwards, Wei Fan, Jing Gao, Kun Zhang. Classifying Imbalanced Data Streams via Dynamic Feature Group Weighting with Importance Sampling. SIAM International Conference on Data Mining, Philadelphia, PA, April 2014, 722-730.

Manish Gupta, Jing Gao, Xifeng Yan, Hasan Cam, Jiawei Han. Top-K Interesting Subgraph Discovery in Information Networks. IEEE International Conference on Data Engineering, Chicago, IL, March 2014, 820-831. Acceptance Rate: 89/446 = 19.96%.

Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Han. Outlier Detection for Temporal Data. Morgan & Claypool, Synthesis Lectures on Data Mining and Knowledge Discovery, March 2014. 

Ming Ni, Qing He, Jing Gao. Using Social Media to Predict Traffic Flow under Special Event Conditions. Transportation Research Board Annual Meeting, Washington, DC, January 2014.

Kang Li, Suxin Guo, Nan Du, Jing Gao, Aidong Zhang. Learning, Analyzing and Predicting Object Roles on Dynamic Networks. IEEE International Conference on Data Mining, Dallas, TX, December 2013, 428-437. Acceptance Rate: 94/809 = 11.62%.

Nan Du, Jing Gao, Aidong Zhang. Progression Analysis of Community Strengths in Dynamic Networks. IEEE International Conference on Data Mining, Dallas, TX, December 2013, 1031-1036. Acceptance Rate: 159/809 = 19.65%.

Sihong Xie, Xiangnan Kong, Jing Gao, Wei Fan, Philip S. Yu. Multilabel Consensus Classification. IEEE International Conference on Data Mining, Dallas, TX, December 2013, 1241-1246. Acceptance Rate: 159/809 = 19.65%.

Liang Ge, Jing Gao, Aidong Zhang. OMS-TL: A Framework of Online Multiple Source Transfer Learning. ACM International Conference on Information and Knowledge Management, San Francisco, CA, October 2013, 2423-2428. Acceptance Rate: 250/848 = 29.48%.

Xiaoyi Li, Jing Gao, Hui Li, Le Yang, Rohini K. Srihari. A Multimodal Framework for Unsupervised Feature Fusion. ACM International Conference on Information and Knowledge Management, San Francisco, CA, October 2013, 897-902. Acceptance Rate: 250/848 = 29.48%.

Kang Li, Suxin Guo, Jing Gao, Aidong Zhang. An Ensemble Model for Mobile Device based Arrhythmia Detection. ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, Washington, DC, September 2013, 266-275. Acceptance Rate: 43/148 = 29%.

Manish Gupta, Jing Gao, Jiawei Han. Community Distribution Outlier Detection in Heterogeneous Information Networks. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Prague, Czech Republic, September 2013, 557-573. Acceptance Rate: 111/443 = 25%.

Xian Wu, Ziming Feng, Wei Fan, Jing Gao, Yong Yu. Detecting Marionette Microblog Users for Improved Information Credibility. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Prague, Czech Republic, September 2013, 483-498. Acceptance Rate: 111/443 = 25%.

Manish Gupta, Jing Gao, Xifeng Yan, Hasan Cam, Jiawei Han. On Detecting Association-Based Clique Outliers in Heterogeneous Information Networks. IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Niagara Falls, Canada, August 2013, 108-115. Acceptance Rate: ~13%.

Liang Ge, Jing Gao, Xiaoyi Li, Aidong Zhang. Multi-Source Deep Learning for Information Trustworthiness Estimation. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, IL, August 2013, 766-774. Acceptance Rate: 126/726 = 17.4%. 

Mohammad M. Masud, Qing Chen, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Ashok Srivastava, Nikunj C. Oza. Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams. IEEE Transactions on Knowledge and Data Engineering, 25(7): 1484-1497, July 2013.

David M. Johnson, Caiming Xion, Jing Gao, Jason J. Corso. Comprehensive Cross-Hierarchy Cluster Agreement Evaluation. AAAI Conference on Artificial Intelligence, Bellevue, WA, May 2013, 56-58.

Liang Ge, Jing Gao, Hung Q. Ngo, Kang Li, Aidong Zhang. On Handling Negative Transfer and Imbalanced Distributions in Multiple Source Transfer Learning. SIAM International Conference on Data Mining, Austin, TX, May 2013, 261-269. Acceptance Rate: 50/348 = 14.4%. Selected for publication in the special issue of "Best of SDM 2013" in Statistical Analysis and Data Mining 

Jialu Liu, Chi Wang, Jing Gao, Jiawei Han. Multi-view Clustering via Joint Nonnegative Matrix Factorization. SIAM International Conference on Data Mining, Austin, TX, May 2013, 252-260. Acceptance Rate: 50/348 = 14.4%.

Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han. A Graph-based Consensus Maximization Approach for Combining Multiple Supervised and Unsupervised Models. IEEE Transactions on Knowledge and Data Engineering, 25(1): 15-28, January 2013.

Liang Ge, Jing Gao, Xiao Yu, Wei Fan, Aidong Zhang. Estimating Local Information Trustworthiness via Multi-Source Joint Matrix Factorization. IEEE International Conference on Data Mining, December 2012, 876-881. Acceptance Rate: 20%.

Lu Su, Shaohan Hu, Shen Li, Feng Liang, Jing Gao, Tarek Abdelzaher, Jiawei Han. Quality of Information based Data Selection and Transmission in Wireless Sensor Networks. IEEE Real-time Systems Symposium, San Juan, Puerto Rico, December 2012, 327-338. Acceptance Rate: 22%.

Jing Gao, Nan Du, Wei Fan, Deepak Turaga, Srinivasan Parthasarathy, Jiawei Han A Multi-graph Spectral Framework for Mining Multi-source Anomalies. Y. Fu and Y. Ma (eds.), Graph Embedding for Pattern Analysis, Springer, 2012, 205-228.

Nan Du, Yuan Zhang, Kang Li, Jing Gao, Aidong Zhang. Evolutionary Analysis of Functional Modules in Dynamic PPI Networks. ACM Conference on Bioinformatics, Computational Biology and Biomedicine, Orlando, Florida, October 2012, 250-257. Acceptance Rate: 33/159 = 20.75%.

Liang Ge, Jing Gao, Nan Du, Aidong Zhang. Finding Informative Genes for Prostate Cancer: A General Framework of Integrating Heterogeneous Sources. ACM Conference on Bioinformatics, Computational Biology and Biomedicine, Orlando, Florida, October 2012, 274-281. Acceptance Rate: 64/159 = 40.25%.

Nan Du, Jing Gao, Vishrawas Gopalakrishna, Aidong Zhang. De-noise Biological Network from Heterogeneous Sources via Link Propagation. IEEE International Conference on Bioinformatics and Biomedicine, Philadelphia, PA, October 2012, 1-6. Acceptance Rate: 59/299 = 19.93%.

Manish Gupta, Jing Gao, ChengXiang Zhai, Jiawei Han. Predicting Future Popularity Trend of Events in Microblogging Platforms. 75th Annual Meeting of American Society for Information Science & Technology, Baltimore, MD, October 2012, 49(1): 1-10.

Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han. Community Trend Outlier Detection Using Soft Temporal Pattern Mining. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bristol, UK, September 2012, 692-708. Acceptance Rate: 105/443 = 23.7%.

Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han. Integrating Community Matching and Outlier Detection for Mining Evolutionary Community Outliers. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, China, August 2012, 859-867. Acceptance Rate: 133/755 = 17.6%.

Jing Gao. Exploring the Power of Heterogeneous Information Sources. Ph.D. Dissertation, University of Illinois, Urbana-Champaign. 

Jing Gao, Wei Fan, Deepak Turaga, Srinivasan Parthasarathy, Jiawei Han. A Spectral Framework for Detecting Inconsistency across Multi-Source Object Relationships. IEEE International Conference on Data Mining, Vancouver, Canada, December 2011, 1050-1055. Acceptance Rate: 148/822 = 18%.

Mohammad Masud, Tahseen Al-Khateeb, Latifur Khan, Charu Aggarwal, Jing Gao, Jiawei Han. Detecting Recurring and Novel Classes in Concept-Drifting Data Streams. IEEE International Conference on Data Mining, Vancouver, Canada, December 2011, 1176-1181. Acceptance Rate: 148/822 = 18%.

Lu Su, Yong Yang, Bolin Ding, Jing Gao, Tarek F. Abdelzaher, Jiawei Han. Hierarchical Aggregate Classification with Limited Supervision for Data Reduction in Wireless Sensor Networks. ACM International Conference on Embedded Networked Sensor Systems, Seattle, WA, November 2011, 40-53. Acceptance Rate: 24/123 = 19.5%.

Mohammad Mehedy Masud, Clay Woolam, Jing Gao, Latifur Khan, Jiawei Han, Kevin W. Hamlen, Nikunj C. Oza. Facing the Reality of Data Stream Classification: Coping with Scarcity of Labeled Data. Knowledge and Information Systems, 33(1): 213-244, October 2011.

Mohammad Mehedy Masud, Tahseen Al-Khateeb, Kevin W. Hamlen, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. Cloud-based Malware Detection for Evolving Data Streams. ACM Transactions on Management Information Systems, 2(3): 16, October 2011.

Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints. IEEE Transactions on Knowledge and Data Engineering, 23(6): 859-874, June 2011.

Jing Gao, Wei Fan, Deepak Turaga, Olivier Verscheure, Xiaoqiao Meng, Lu Su, Jiawei Han. Consensus Extraction from Heterogeneous Detectors to Improve Performance over Network Traffic Anomaly Detection. IEEE International Conference on Computer Communications Mini-Conference, Shanghai, China, April 2011, 181-185. Acceptance Rate: 427/1823 = 23.4%. 

Mohammad Masud, Qing Chen, Latifur Khan, Charu Aggarwal, Jing Gao, Jiawei Han, Bhavani Thuraisingham. Addressing Concept-Evolution in Concept-Drifting Data Streams.. IEEE International Conference on Data Mining, Sydney, Australia, December 2010, 929-934. Acceptance Rate: 155/797 = 19.4%.

Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han, Jing Gao. Graph Regularized Transductive Classification on Heterogeneous Information Networks. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Barcelona, Spain, September 2010, 570-586. Acceptance Rate: 120/658 = 18.2%.

Mohammad Masud, Qing Chen, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space.. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Barcelona, Spain, September 2010, 570-586. Acceptance Rate: 120/658 = 18.2%.

Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Sun, Jiawei Han. On Community Outliers and their Efficient Detection in Information Networks. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, July 2010, 813-822. Acceptance Rate: 77/578 = 13.3%. 

Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. Classification and Novel Class Detection in Data Streams with Active Mining. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Hyderabad, India, June 2010, 311-324. Acceptance Rate: 42/412 = 10.2%.

Jing Gao, Feng Liang, Wei Fan, Yizhou Sun, Jiawei Han. Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models. Advances in Neural Information Processing Systems, 22, 2009, 585-593. Acceptance Rate: 263/1105 = 23.8%. 

Yizhou Sun, Jiawei Han,Jing Gao, Yintao Yu. iTopic Model: Information Network-Integrated Topic Modeling. IEEE International Conference on Data Mining, Miami, FL, December 2009, 493-502. Acceptance Rate: 70/786 = 8.9%.

Chandrasekar Ramachandran, Rahul Malik, Xin Jin, Jing Gao, Klara Nahrstedt, Jiawei Han. VideoMule: A Consensus Learning Approach to Multi-Label Classification from Noisy User-Generated Videos. ACM International Conference on Multimedia, Beijing, China, October 2009, 721-724. Acceptance Rate: 58/204 = 28%.

Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Bled, Slovenia, September 2009, 79-94. Acceptance Rate: 105/422 = 24.9%.

Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han. Heterogeneous Source Consensus Learning via Decision Propagation and Negotiation. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 2009, 339-347. Acceptance Rate: 112/538 = 20.8%. 

Jing Gao, Guofei Jiang, Haifeng Chen, Jiawei Han. Modeling Probabilistic Measurement Correlations for Problem Determination in Large-Scale Distributed Systems. International Conference on Distributed Computing Systems, Montreal, Canada, June 2009, 623-630. Acceptance Rate: 74/455 = 16%. 

Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham. A Multi-Partition Multi-Chunk Ensemble Technique to Classify Concept-Drifting Data Streams. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Bangkok, Thailand, April 2009, 363-375. Acceptance Rate: 39/338 = 11.5%.

Jiawei Han, Jing Gao. Research Challenges for Data Mining in Science and Engineering. H. Kargupta, et al., (eds.), Next Generation of Data Mining, Chapman & Hall, 2009, 3-28.

Jing Gao, Bolin Ding, Wei Fan, Jiawei Han, Philip S. Yu. Classifying Data Streams with Skewed Class Distributions and Concept Drifts. IEEE Internet Computing, Special Issue on Data Stream Management, Nov./Dec. 2008, 12(6): 37-49.

Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han. A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data. IEEE International Conference on Data Mining, Pisa, Italy, December 2008, 929-934. Acceptance Rate: 144/724 = 19.9%.

Jing Gao, Wei Fan, Jing Jiang, Jiawei Han. Knowledge Transfer via Multiple Model Local Structure Mapping. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, NV, August 2008, 283-291. Acceptance Rate: 95/510 = 18.6%. 

Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Yan, Jiawei Han, Philip S. Yu, Olivier Verscheure. Direct Mining of Discriminative and Essential Graphical and Item set Features via Model-based Search Tree. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, NV, August 2008, 283-291. Acceptance Rate: 50/510 = 9.8%.

Jing Gao, Wei Fan, Jiawei Han. On Appropriate Assumptions to Mine Data Streams: Analysis and Practice. IEEE International Conference on Data Mining, Omaha, NE, October 2007, 143-152. Acceptance Rate: 40/573 = 7.5%. 

Jing Gao, Wei Fan, Jiawei Han, Phillip S. Yu. A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions. SIAM International Conference on Data Mining, Minneapolis, MN, April 2007, 3-14. Acceptance Rate: 36/302 = 11.9%. 

Jing Gao, Pang-Ning Tan. Converting Output Scores from Outlier Detection Algorithms into Probability Estimates. IEEE International Conference on Data Mining, Hong Kong, China, December 2006, 212-221. Acceptance Rate: 73/776 = 9.4%. 

Jing Gao, Pang-Ning Tan, Haibin Cheng. Semi-Supervised Clustering with Partial Background Information. SIAM International Conference on Data Mining, Bethesda, MD, April 2006, 489-493. 

Jing Gao, Haibin Cheng, Pang-Ning Tan. A Novel Framework for Incorporating Labeled Examples into Anomaly Detection. SIAM International Conference on Data Mining, Bethesda, MD, April 2006, 594-598.

Haibin Cheng, Pang-Ning Tan, Jing Gao, Jerry Scripps. An Empirical Study on Multistep-ahead Time Series Prediction. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Singapore, April 2006, 765-774.

Jing Gao, Haibin Cheng, Pang-Ning Tan. Semi-Supervised Outlier Detection. ACM Symposium on Applied Computing, Dijon, France, April 2006, 635-636.

Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning Tan. An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. Pacific-Asia Conference on Knowledge Discovery and Data Mining, Hanoi, Vietnam, May 2005, 420-425.

Jing Gao, Jianzhong Li, Zhaogong Zhang. Mining Maximal Frequent Patterns over Numerical Data Streams. Journal of Computer Research and Development. Vol.41, Suppl.: 282-288, 2004. (in Chinese)

Jing Gao, Jianzhong Li, Zhaogong Zhang, Yanqiu Zhang. An Efficient Data Stream Clustering Algorithm Based on Grids and Density. Journal of Computer Science, Vol. 30, Suppl.: 256-260, 2003. (in Chinese)