Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Simon Fraser University 2002
• Recognition
• 

  In the News

  • MAY 4, 2023

    Duke Today

    Duke Awards 44 Distinguished Professorships

  • FEB 14, 2023

    Duke Today

    Spring Books from Duke Authors from Wittgenstein to Capoeira

  • OCT 29, 2022

    Department of Computer Science

    Data, Data Everywhere: Jian Pei on Equity and Efficiency in Data Science
• Research
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  External Relationships

  • Research Grants Council of Hong Kong
  • Simon Fraser University
  • fortinet inc
• Publications & Artistic Works
• 

  Selected Publications

  • Books

    • Sadiq, S., J. Pei, and Y. Manolopoulos. Preface. Vol. 10828 LNCS, 2018.
    • Sadiq, S., J. Pei, and Y. Manolopoulos. Preface. Vol. 10827 LNCS, 2018.
    • Han, J., M. Kamber, and J. Pei. Data Mining: Concepts and Techniques, 2012. https://doi.org/10.1016/C2009-0-61819-5.
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    • Pei, Jian. Special Issue: Best Papers from the Fifth International Conference on Advanced Data Mining and Applications (ADMA 2009). Springer, 2011.
    • Shen, H. T., and J. Pei. WAIM 2010 Workshop chair's message. Vol. 6185 LNCS, 2010. https://doi.org/10.1007/978-3-642-16720-1.
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    • Qiang, Y., H. Ronghuai, P. Jian, J. Gama, and M. Xiaofeng. Advanced Data Mining and Applications: 5th International Conference, ADMA 2009 Beijing, China, August 17-19, 2009 Proceedings - Preface. Vol. 5678 LNAI, 2009.
    • Li, Q., L. Feng, J. Pei, S. X. Wang, X. Zhou, and Q. Zhu. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface. Vol. 5446, 2009.
    • Yan, J., and P. Jian. Web-based massive data processing workshop chairs' message. Vol. 4256 LNCS, 2006.

  • Academic Articles

    • Xia, L., C. Huang, Y. Xu, and J. Pei. “Multi-Behavior Sequential Recommendation With Temporal Graph Transformer (Accepted).” Ieee Transactions on Knowledge and Data Engineering 35, no. 6 (June 1, 2023): 6099–6112. https://doi.org/10.1109/TKDE.2022.3175094.
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    • Zhang, Z., C. Niu, P. Cui, J. Pei, B. Zhang, and W. Zhu. “Permutation-Equivariant and Proximity-Aware Graph Neural Networks With Stochastic Message Passing (Accepted).” Ieee Transactions on Knowledge and Data Engineering 35, no. 6 (June 1, 2023): 6182–93. https://doi.org/10.1109/TKDE.2022.3154391.
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    • Huang, R., J. Wang, S. Song, X. Lin, X. Zhu, and J. Pei. “Efficiently Cleaning Structured Event Logs: A Graph Repair Approach.” Acm Transactions on Database Systems 48, no. 1 (March 14, 2023). https://doi.org/10.1145/3571281.
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    • Zhang, Z., P. Cui, J. Pei, X. Wang, and W. Zhu. “Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs.” Ieee Transactions on Knowledge and Data Engineering 35, no. 3 (March 1, 2023): 2544–55. https://doi.org/10.1109/TKDE.2021.3112746.
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    • Jiang, H., H. Yu, X. Cheng, J. Pei, R. Pless, and J. Yu. “DP2-Pub: Differentially Private High-Dimensional Data Publication With Invariant Post Randomization.” Ieee Transactions on Knowledge and Data Engineering, January 1, 2023. https://doi.org/10.1109/TKDE.2023.3265605.
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    • Jiang, H., J. Pei, D. Yu, J. Yu, B. Gong, and X. Cheng. “Applications of Differential Privacy in Social Network Analysis: A Survey.” Ieee Transactions on Knowledge and Data Engineering 35, no. 1 (January 1, 2023): 108–27. https://doi.org/10.1109/TKDE.2021.3073062.
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    • Shi, H., M. A. Tayebi, J. Pei, and J. Cao. “Cost-Sensitive Learning for Medical Insurance Fraud Detection with Temporal Information.” Ieee Transactions on Knowledge and Data Engineering, January 1, 2023. https://doi.org/10.1109/TKDE.2023.3240431.
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    • Pei, J. “A Survey on Data Pricing: From Economics to Data Science.” Ieee Transactions on Knowledge and Data Engineering 34, no. 10 (October 1, 2022): 4586–4608. https://doi.org/10.1109/TKDE.2020.3045927.
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    • Cong, Z., X. Luo, J. Pei, F. Zhu, and Y. Zhang. “Data pricing in machine learning pipelines.” Knowledge and Information Systems 64, no. 6 (June 1, 2022): 1417–55. https://doi.org/10.1007/s10115-022-01679-4.
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    • Bajaj, Mohit, Lingyang Chu, Vittorio Romaniello, Gursimran Singh, Jian Pei, Zirui Zhou, Lanjun Wang, and Yong Zhang. “Revealing Unfair Models by Mining Interpretable Evidence.” Arxiv Preprint Arxiv:2207.05811, 2022.
    • Charette, Laurent, Lingyang Chu, Yizhou Chen, Jian Pei, Lanjun Wang, and Yong Zhang. “Cosine Model Watermarking Against Ensemble Distillation.” Arxiv Preprint Arxiv:2203.02777, 2022.
    • Chen, Nuo, Linjun Shou, Ming Gong, Jian Pei, and Daxin Jiang. “Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling.” Arxiv Preprint Arxiv:2204.05210, 2022.
    • Cong, Zicun, Xuan Luo, Jian Pei, Feida Zhu, and Yong Zhang. “Data pricing in machine learning pipelines.” Knowledge and Information Systems, 2022, 1–39.
    • Fan, Zhenan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, and Yong Zhang. “Fair and efficient contribution valuation for vertical federated learning.” Arxiv Preprint Arxiv:2201.02658, 2022.
    • Huang, F., S. Gao, J. Pei, and H. Huang. “Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization.” Journal of Machine Learning Research 23 (January 1, 2022).
    • Huang, Feihu, Shangqian Gao, Jian Pei, and Heng Huang. “Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization.” J. Mach. Learn. Res. 23 (2022): 36–1.
    • Li, Junyi, Jian Pei, and Heng Huang. “Communication-Efficient Robust Federated Learning with Noisy Labels.” Arxiv Preprint Arxiv:2206.05558, 2022.
    • Li, Zhonghang, Chao Huang, Lianghao Xia, Yong Xu, and Jian Pei. “Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction.” Arxiv Preprint Arxiv:2204.08587, 2022.
    • Liang, Shining, Linjun Shou, Jian Pei, Ming Gong, Wanli Zuo, Xianglin Zuo, and Daxin Jiang. “Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding.” Arxiv Preprint Arxiv:2205.03656, 2022.
    • Lin, Weizhe, Linjun Shou, Ming Gong, Pei Jian, Zhilin Wang, Bill Byrne, and Daxin Jiang. “Transformer-Empowered Content-Aware Collaborative Filtering.” Arxiv Preprint Arxiv:2204.00849, 2022.
    • Liu, C., Z. Zhou, J. Pei, Y. Zhang, and Y. Shi. “Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach with Linear Convergence.” Ieee Transactions on Automatic Control, January 1, 2022. https://doi.org/10.1109/TAC.2022.3209951.
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    • Shi, H., Y. Yang, L. Wang, D. Ma, M. F. Beg, J. Pei, and J. Cao. “Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction.” Journal of Computational and Graphical Statistics 31, no. 4 (January 1, 2022): 1127–40. https://doi.org/10.1080/10618600.2022.2035738.
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    • Zhang, He, Bang Wu, Xingliang Yuan, Shirui Pan, Hanghang Tong, and Jian Pei. “Trustworthy Graph Neural Networks: Aspects, Methods and Trends.” Arxiv Preprint Arxiv:2205.07424, 2022.
    • Zhuang, Shengyao, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Guido Zuccon, and Daxin Jiang. “Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation.” Arxiv Preprint Arxiv:2206.10128, 2022.
    • Hu, X., L. Chu, J. Pei, W. Liu, and J. Bian. “Model complexity of deep learning: a survey.” Knowledge and Information Systems 63, no. 10 (October 1, 2021): 2585–2619. https://doi.org/10.1007/s10115-021-01605-0.
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    • Liu, J., L. Xiong, J. Pei, J. Luo, H. Zhang, and W. Yu. “Group-Based Skyline for Pareto Optimal Groups.” Ieee Transactions on Knowledge and Data Engineering 33, no. 7 (July 1, 2021): 2914–29. https://doi.org/10.1109/TKDE.2019.2960347.
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    • Yu, W., X. He, J. Pei, X. Chen, L. Xiong, J. Liu, and Z. Qin. “Visually aware recommendation with aesthetic features.” Vldb Journal 30, no. 4 (July 1, 2021): 495–513. https://doi.org/10.1007/s00778-021-00651-y.
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    • Shi, Haolun, Da Ma, Yunlong Nie, Mirza Faisal Beg, Jian Pei, Jiguo Cao, and The Alzheimer’s Disease Neuroimaging Initiative. “Early diagnosis of Alzheimer's disease on ADNI data using novel longitudinal score based on functional principal component analysis.” Journal of Medical Imaging (Bellingham, Wash.) 8, no. 2 (March 2021): 024502. https://doi.org/10.1117/1.jmi.8.2.024502.
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    • Yang, Y., and J. Pei. “Influence Analysis in Evolving Networks: A Survey.” Ieee Transactions on Knowledge and Data Engineering 33, no. 3 (March 1, 2021): 1045–63. https://doi.org/10.1109/TKDE.2019.2934447.
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    • Cho-Ho Lam, Peter, Lingyang Chu, Maxim Torgonskiy, Jian Pei, Yong Zhang, and Lanjun Wang. “Finding Representative Interpretations on Convolutional Neural Networks.” Arxiv E Prints, 2021, arXiv-2108.
    • Chu, Lingyang, Lanjun Wang, Yanjie Dong, Jian Pei, Zirui Zhou, and Yong Zhang. “Fedfair: Training fair models in cross-silo federated learning.” Arxiv Preprint Arxiv:2109.05662, 2021.
    • Fan, Zhenan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, and Yong Zhang. “Improving fairness for data valuation in federated learning.” Arxiv Preprint Arxiv:2109.09046, 2021.
    • Hu, Xia, Lingyang Chu, Jian Pei, Jiang Bian, and Weiqing Liu. “Deep Learning Model Complexity: Concepts and Approaches,” 2021.
    • Liu, Changxin, Zirui Zhou, Yang Shi, Jian Pei, Lingyang Chu, and Yong Zhang. “Achieving Model Fairness in Vertical Federated Learning.” Arxiv Preprint Arxiv:2109.08344, 2021.
    • Liu, J., J. Lou, L. Xiong, J. Pei, and J. Sun. “Dealer: An end-to-end model marketplace with differential privacy.” Proceedings of the Vldb Endowment 14, no. 6 (January 1, 2021): 957–69. https://doi.org/10.14778/3447689.3447700.
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    • Liu, J., J. Yang, L. Xiong, J. Pei, J. Luo, Y. Guo, S. Ma, and C. Fan. “Skyline diagram: Efficient space partitioning for skyline queries.” Ieee Transactions on Knowledge and Data Engineering 33, no. 1 (January 1, 2021): 271–86. https://doi.org/10.1109/TKDE.2019.2923914.
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    • Wang, Haixin, Cheng Xu, Ce Zhang, Jianliang Xu, Zhe Peng, and Jian Pei. “vChain+: Optimizing Verifiable Blockchain Boolean Range Queries (Technical Report),” 2021.
    • Wu, Lingfei, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, and Bo Long. “Graph neural networks for natural language processing: A survey.” Arxiv Preprint Arxiv:2106.06090, 2021.
    • Xu, Cheng, Ce Zhang, Jianliang Xu, and Jian Pei. “SlimChain: scaling blockchain transactions through off-chain storage and parallel processing.” Proceedings of the Vldb Endowment 14 (2021): 2314–26.
    • Choi, D. W., J. Pei, and X. Lin. “On spatial keyword covering.” Knowledge and Information Systems 62, no. 7 (July 1, 2020): 2577–2612. https://doi.org/10.1007/s10115-020-01446-3.
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    • Yu, W., J. Liu, J. Pei, L. Xiong, X. Chen, and Z. Qin. “Efficient Contour Computation of Group-Based Skyline.” Ieee Transactions on Knowledge and Data Engineering 32, no. 7 (July 1, 2020): 1317–32. https://doi.org/10.1109/TKDE.2019.2905239.
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    • Yang, Y., X. Mao, J. Pei, and X. He. “Continuous influence maximization.” Acm Transactions on Knowledge Discovery From Data 14, no. 3 (May 8, 2020). https://doi.org/10.1145/3380928.
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    • Amer-Yahia, S., and J. Pei. “VLDB SI 2018 editorial.” Vldb Journal 29, no. 2–3 (May 1, 2020): 593–94. https://doi.org/10.1007/s00778-019-00599-0.
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    • Amer-Yahia, Sihem, and Jian Pei. “VLDB SI 2018 editorial.” The Vldb Journal 29 (2020): 593–94.
    • Cong, Zicun, Lingyang Chu, Yu Yang, and Jian Pei. “Comprehensible counterfactual explanation on Kolmogorov-Smirnov test.” Arxiv Preprint Arxiv:2011.01223, 2020.
    • Huang, Yutao, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, and Yong Zhang. “Personalized federated learning: An attentive collaboration approach,” 2020.
    • Jiang, Honglu, Jian Pei, Dongxiao Yu, Jiguo Yu, Bei Gong, and Xiuzhen Cheng. “Differential privacy and its applications in social network analysis: A survey.” Arxiv Preprint Arxiv:2010.02973, 2020.
    • Lei, M., L. Chu, Z. Wang, J. Pei, C. He, X. Zhang, and B. Fang. “Mining top-k sequential patterns in transaction database graphs: A new challenging problem and a sampling-based approach.” World Wide Web 23, no. 1 (January 1, 2020): 103–30. https://doi.org/10.1007/s11280-019-00686-w.
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    • Lei, Mingtao, Lingyang Chu, Zhefeng Wang, Jian Pei, Caifeng He, Xi Zhang, and Binxing Fang. “Mining top-k sequential patterns in transaction database graphs.” World Wide Web 23 (2020): 103–30.
    • Li, Hui-Jia, Zhen Wang, Jian Pei, Jie Cao, and Yong Shi. “Optimal estimation of low-rank factors via feature level data fusion of multiplex signal systems.” Ieee Transactions on Knowledge and Data Engineering, 2020.
    • Liu, Junhao, Linjun Shou, Jian Pei, Ming Gong, Min Yang, and Daxin Jiang. “Cross-lingual machine reading comprehension with language branch knowledge distillation.” Arxiv Preprint Arxiv:2010.14271, 2020.
    • Zhang, Xingyao, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen, and Daxin Jiang. “A graph representation of semi-structured data for web question answering.” Arxiv Preprint Arxiv:2010.06801, 2020.
    • Zhao, Z., L. Chu, D. Tao, and J. Pei. “Classification with label noise: a Markov chain sampling framework.” Data Mining and Knowledge Discovery 33, no. 5 (September 1, 2019): 1468–1504. https://doi.org/10.1007/s10618-018-0592-8.
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    • Liu, Jinfei, Juncheng Yang, Li Xiong, and Jian Pei. “Secure and Efficient Skyline Queries on Encrypted Data.” Ieee Transactions on Knowledge and Data Engineering 31, no. 7 (July 2019): 1397–1411. https://doi.org/10.1109/tkde.2018.2857471.
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    • Yu, W., X. Lin, W. Zhang, J. Pei, and J. A. McCann. “SimRank*: effective and scalable pairwise similarity search based on graph topology.” Vldb Journal 28, no. 3 (June 1, 2019): 401–26. https://doi.org/10.1007/s00778-018-0536-3.
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    • Cui, P., X. Wang, J. Pei, and W. Zhu. “A Survey on Network Embedding.” Ieee Transactions on Knowledge and Data Engineering 31, no. 5 (May 1, 2019): 833–52. https://doi.org/10.1109/TKDE.2018.2849727.
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    • Huang, Feihu, Shangqian Gao, Jian Pei, and Heng Huang. “Nonconvex zeroth-order stochastic admm methods with lower function query complexity.” Arxiv Preprint Arxiv:1907.13463, 2019.
    • Osman, Abdullahi Sidow. “Data mining techniques,” 2019.
    • Zhu, D., P. Cui, Z. Zhang, J. Pei, and W. Zhu. “High-Order Proximity Preserved Embedding for Dynamic Networks.” Ieee Transactions on Knowledge and Data Engineering 30, no. 11 (November 1, 2018): 2134–44. https://doi.org/10.1109/TKDE.2018.2822283.
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    • Hu, J., and J. Pei. “Subspace multi-clustering: a review.” Knowledge and Information Systems 56, no. 2 (August 1, 2018): 257–84. https://doi.org/10.1007/s10115-017-1110-9.
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    • Yang, Yu, Zhefeng Wang, Tianyuan Jin, Jian Pei, and Enhong Chen. “Tracking top-K influential vertices in dynamic networks.” Arxiv Preprint Arxiv:1803.01499, 2018.
    • Moskovitch, R., F. Wang, J. Pei, and C. Friedman. “JASIST special issue on biomedical information retrieval.” Journal of the Association for Information Science and Technology 68, no. 11 (November 1, 2017): 2525–28. https://doi.org/10.1002/asi.23972.
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    • Wang, Z., Y. Yang, J. Pei, L. Chu, and E. Chen. “Activity Maximization by Effective Information Diffusion in Social Networks.” Ieee Transactions on Knowledge and Data Engineering 29, no. 11 (November 1, 2017): 2374–87. https://doi.org/10.1109/TKDE.2017.2740284.
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    • Yang, Y., Z. Wang, J. Pei, and E. Chen. “Tracking Influential Individuals in Dynamic Networks.” Ieee Transactions on Knowledge and Data Engineering 29, no. 11 (November 1, 2017): 2615–28. https://doi.org/10.1109/TKDE.2017.2734667.
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    • Yang, Y., J. Pei, and A. Al-Barakati. “Measuring in-network node similarity based on neighborhoods: a unified parametric approach.” Knowledge and Information Systems 53, no. 1 (October 1, 2017): 43–70. https://doi.org/10.1007/s10115-017-1033-5.
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    • Hu, J., Q. Qian, J. Pei, R. Jin, and S. Zhu. “Finding multiple stable clusterings.” Knowledge and Information Systems 51, no. 3 (June 1, 2017): 991–1021. https://doi.org/10.1007/s10115-016-0998-9.
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    • Campbell, A., X. Mao, J. Pei, and A. Al-Barakati. “Multidimensional benchmarking in data warehouses.” Intelligent Data Analysis 21, no. 4 (January 1, 2017): 781–801. https://doi.org/10.3233/IDA-160035.
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    • Campbell, A., X. Mao, J. Pei, and A. Al-Barakati. “Multidimensional business benchmarking analysis on data warehouses.” International Journal of Data Warehousing and Mining 13, no. 1 (January 1, 2017): 51–75. https://doi.org/10.4018/IJDWM.2017010103.
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    • Chu, Lingyang, Zhefeng Wang, Jian Pei, Yanyan Zhang, Yu Yang, and Enhong Chen. “Finding theme communities from database networks: from mining to indexing and query answering.” Arxiv Preprint Arxiv:1709.08083, 2017.
    • Liu, Jinfei, Li Xiong, Qiuchen Zhang, Jian Pei, and Jun Luo. “Eclipse: Practicability Beyond kNN and Skyline.” Arxiv Preprint Arxiv:1707.01223, 2017.
    • Yu, K., X. Wu, W. Ding, and J. Pei. “Scalable and accurate online feature selection for big data.” Acm Transactions on Knowledge Discovery From Data 11, no. 2 (December 1, 2016). https://doi.org/10.1145/2976744.
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    • Liu, Shixia, Jialun Yin, Xiting Wang, Weiwei Cui, Kelei Cao, and Jian Pei. “Online Visual Analytics of Text Streams.” Ieee Transactions on Visualization and Computer Graphics 22, no. 11 (November 2016): 2451–66. https://doi.org/10.1109/tvcg.2015.2509990.
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    • Vinh, N. X., J. Chan, S. Romano, J. Bailey, C. Leckie, K. Ramamohanarao, and J. Pei. “Discovering outlying aspects in large datasets.” Data Mining and Knowledge Discovery 30, no. 6 (November 1, 2016): 1520–55. https://doi.org/10.1007/s10618-016-0453-2.
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    • Pei, J., G. Li, and H. Tong. “Preface.” Big Data Research 5 (September 1, 2016): 1. https://doi.org/10.1016/j.bdr.2016.09.001.
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    • Xu, X., C. Gao, J. Pei, K. Wang, and A. Al-Barakati. “Continuous similarity search for evolving queries.” Knowledge and Information Systems 48, no. 3 (September 1, 2016): 649–78. https://doi.org/10.1007/s10115-015-0892-x.
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    • Pei, J. “Preface.” Journal of Computer Science and Technology 31, no. 4 (July 1, 2016): 635–36. https://doi.org/10.1007/s11390-016-1652-4.
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    • Schuller, B., and J. Pei. “Using computer intelligence for depression diagnosis and crowdsourcing.” Computer 49, no. 7 (July 1, 2016): 8–9. https://doi.org/10.1109/MC.2016.206.
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    • Duan, L., G. Tang, J. Pei, J. Bailey, G. Dong, V. Nguyen, A. Campbell, and C. Tang. “Efficient discovery of contrast subspaces for object explanation and characterization.” Knowledge and Information Systems 47, no. 1 (April 1, 2016): 99–129. https://doi.org/10.1007/s10115-015-0835-6.
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    • Han, J., M. Kamber, J. Pei, Morgan Kaufmann Data Mining, T. Hastie, R. Tibshirani, and J. Friedman. “Bachelor-und Masterarbeitsthemen im WS 2016/2017,” 2016.
    • Pei, Jian, Leman Akoglu, Hongrae Lee, Justin Levandoski, Xuelong Li, Rosa Meo, Carlos Ordonez, et al. “EIC Editorial.” Ieee Transactions on Knowledge & Data Engineering 28 (2016): 2535–37.
    • Duan, L., G. Tang, J. Pei, J. Bailey, A. Campbell, and C. Tang. “Mining outlying aspects on numeric data.” Data Mining and Knowledge Discovery 29, no. 5 (September 22, 2015): 1116–51. https://doi.org/10.1007/s10618-014-0398-2.
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    • Tang, G., J. Pei, J. Bailey, and G. Dong. “Mining multidimensional contextual outliers from categorical relational data.” Intelligent Data Analysis 19, no. 5 (September 8, 2015): 1171–92. https://doi.org/10.3233/IDA-150764.
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    • Zhang, X., W. Dou, J. Pei, S. Nepal, C. Yang, C. Liu, and J. Chen. “Proximity-aware local-recoding anonymization with MapReduce for scalable big data privacy preservation in cloud.” Ieee Transactions on Computers 64, no. 8 (August 1, 2015): 2293–2307. https://doi.org/10.1109/TC.2014.2360516.
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    • Pei, J. “Preface.” Journal of Computer Science and Technology 30, no. 4 (July 1, 2015): 655–56. https://doi.org/10.1007/s11390-015-1552-z.
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    • Yu, K., W. Ding, D. A. Simovici, H. Wang, J. Pei, and X. Wu. “Classification with streaming features: An emerging-pattern mining approach.” Acm Transactions on Knowledge Discovery From Data 9, no. 4 (June 1, 2015): 1–31. https://doi.org/10.1145/2700409.
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    • Yang, Y., Q. Lu, G. Tang, and J. Pei. “The impact of market competition on search advertising.” Journal of Interactive Marketing 30 (May 1, 2015): 46–55. https://doi.org/10.1016/j.intmar.2015.01.002.
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    • Pei, Jian. “State of the Journal Editorial.” Ieee Transactions on Knowledge & Data Engineering 27 (2015): 1–2.
    • Yang, Yu, and Jian Pei. “In-network neighborhood-based node similarity measure: A unified parametric model.” Arxiv Preprint Arxiv:1510.03814, 2015.
    • Huang, D., K. Xu, and J. Pei. “Malicious URL detection by dynamically mining patterns without pre-defined elements.” World Wide Web 17, no. 6 (November 1, 2014): 1375–94. https://doi.org/10.1007/s11280-013-0250-4.
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    • Tang, G., J. Pei, and W. S. Luk. “Email mining: Tasks, common techniques, and tools.” Knowledge and Information Systems 41, no. 1 (October 1, 2014): 1–31. https://doi.org/10.1007/s10115-013-0658-2.
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    • Pei, J. “EIC editorial.” Ieee Transactions on Knowledge and Data Engineering 26, no. 7 (July 1, 2014): 1559–61. https://doi.org/10.1109/TKDE.2014.2327286.
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    • Yang, Y., J. X. Yu, H. Gao, J. Pei, and J. Li. “Mining most frequently changing component in evolving graphs.” World Wide Web 17, no. 3 (May 1, 2014): 351–76. https://doi.org/10.1007/s11280-013-0204-x.
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    • Chen, W. G., X. L. Chen, S. M. Hu, J. Pei, T. Xie, and W. W. Zhu. “Editorial: Moving forward to respond to rapid changes of computer science and technology.” Journal of Computer Science and Technology 29, no. 1 (January 1, 2014): 1. https://doi.org/10.1007/s11390-013-1406-5.
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    • Kumar, Ravi, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, and Xindong Wu. “Proceedings, 14th IEEE International Conference on Data Mining: 14–17 December 2014 Shenzhen, China,” 2014.
    • Pei, J. “Editorial.” Ieee Transactions on Knowledge and Data Engineering 26, no. 1 (January 1, 2014): 1–2. https://doi.org/10.1109/TKDE.2014.3.
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    • Pei, Jian, and Jian others. “A Semantic Summarization Approach to Data Warehousing and Online Analytical Processing,” 2014.
    • Pei, Jian. “Managing Data-Intensive Applications in the Cloud.” Computer 47 (2014): 6–6.
    • Srihari, Sargur, Srirangaraj Setlur, Jian Pei, and Jian others. “Epidemiological Analysis and Early Warning of Disease Outbreaks by Automated Reading and Mining of Pre-Hospital Care Reports,” 2014.
    • Yang, C., X. Zhang, C. Zhong, C. Liu, J. Pei, K. Ramamohanarao, and J. Chen. “A spatiotemporal compression based approach for efficient big data processing on Cloud.” Journal of Computer and System Sciences 80, no. 8 (January 1, 2014): 1563–83. https://doi.org/10.1016/j.jcss.2014.04.022.
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    • Zhang, Y., W. Zhang, J. Pei, X. Lin, Q. Lin, and A. Li. “Consensus-based ranking of multivalued objects: A generalized borda count approach.” Ieee Transactions on Knowledge and Data Engineering 26, no. 1 (January 1, 2014): 83–96. https://doi.org/10.1109/TKDE.2012.250.
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    • Jiang, D., J. Pei, and H. Li. “Mining search and browse logs for web search: A survey.” Acm Transactions on Intelligent Systems and Technology 4, no. 4 (October 21, 2013). https://doi.org/10.1145/2508037.2508038.
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    • Liao, Z., D. Jiang, J. Pei, Y. Huang, E. Chen, H. Cao, and H. Li. “A vlHMM approach to context-aware search.” Acm Transactions on the Web 7, no. 4 (October 1, 2013). https://doi.org/10.1145/2490255.
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    • Jiang, B., J. Pei, Y. Tao, and X. Lin. “Clustering uncertain data based on probability distribution similarity.” Ieee Transactions on Knowledge and Data Engineering 25, no. 4 (March 11, 2013): 751–63. https://doi.org/10.1109/TKDE.2011.221.
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    • Cui, Y., J. Pei, G. Tang, W. S. Luk, D. Jiang, and M. Hua. “Finding email correspondents in online social networks.” World Wide Web 16, no. 2 (March 1, 2013): 195–218. https://doi.org/10.1007/s11280-012-0168-2.
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    • Chen, J., J. Huang, B. Jiang, J. Pei, and J. Yin. “Recommendations for two-way selections using skyline view queries.” Knowledge and Information Systems 34, no. 2 (February 1, 2013): 397–424. https://doi.org/10.1007/s10115-012-0489-6.
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    • Huang, J., B. Jiang, J. Pei, J. Chen, and Y. Tang. “Skyline distance: A measure of multidimensional competence.” Knowledge and Information Systems 34, no. 2 (February 1, 2013): 373–96. https://doi.org/10.1007/s10115-012-0486-9.
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    • Pei, J. “New EIC editorial.” Ieee Transactions on Knowledge and Data Engineering 25, no. 2 (January 2, 2013): 245. https://doi.org/10.1109/TKDE.2013.5.
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    • Li, J., L. Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, and Hiroshi Motoda. “Trends and Applications in Knowledge Discovery and Data Mining.” Springer. Doi 10 (2013): 978–3.
    • Pei, J. “Editorial.” Ieee Transactions on Knowledge and Data Engineering 25, no. 8 (January 1, 2013): 1689–92. https://doi.org/10.1109/TKDE.2013.99.
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    • Pei, Jian. “Editorial [2012 & 2013 Associate Editors].” Ieee Transactions on Knowledge and Data Engineering 25 (2013): 1689–92.
    • Pei, Jian. “Editorial [State of the Transactions].” Ieee Transactions on Knowledge and Data Engineering 26 (2013): 1–2.
    • Tang, Guoming, Kui Wu, Jian Pei, Jiuyang Tang, and Jingsheng Lei. “Is My Electricity Bill Accurate? A Model-Driven Approach to Corrupted Load Data Identification.” Corr, 2013.
    • Tang, Guoming, Kui Wu, Jian Pei, Jiuyang Tang, and Jingsheng Lei. “Household Electricity Consumption Data Cleansing.” Arxiv Preprint Arxiv:1307.7757, 2013.
    • Wang, Y., P. Wang, J. Pei, W. Wang, and S. Huang. “A data-adaptive and dynamic segmentation index for whole matching on time series.” Proceedings of the Vldb Endowment 6, no. 10 (January 1, 2013): 793–804. https://doi.org/10.14778/2536206.2536208.
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    • Liu, Y., Y. Zhao, L. Chen, J. Pei, and J. Han. “Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays.” Ieee Transactions on Parallel and Distributed Systems 23, no. 11 (October 16, 2012): 2138–49. https://doi.org/10.1109/TPDS.2011.307.
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    • Li, L., S. Petschulat, G. Tang, J. Pei, and W. S. Luk. “Efficient and effective aggregate keyword search on relational databases.” International Journal of Data Warehousing and Mining 8, no. 4 (October 1, 2012): 41–81. https://doi.org/10.4018/jdwm.2012100103.
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    • Hua, M., and J. Pei. “Clustering in applications with multiple data sources-A mutual subspace clustering approach.” Neurocomputing 92 (September 1, 2012): 133–44. https://doi.org/10.1016/j.neucom.2011.08.032.
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    • Abiteboul, S., C. Koch, K. L. Tan, and J. Pei. “Guest editors' Introduction to the special section on the 27th international conference on data engineering (ICDE 2011).” Ieee Transactions on Knowledge and Data Engineering 24, no. 10 (August 30, 2012): 1729–30. https://doi.org/10.1109/TKDE.2012.165.
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    • Xing, Z., J. Pei, and P. S. Yu. “Early classification on time series.” Knowledge and Information Systems 31, no. 1 (April 1, 2012): 105–27. https://doi.org/10.1007/s10115-011-0400-x.
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    • Melli, G., X. Wu, P. Beinat, F. Bonchi, L. Cao, R. Duan, C. Faloutsos, et al. “Top-10 data mining case studies.” International Journal of Information Technology and Decision Making 11, no. 2 (March 1, 2012): 389–400. https://doi.org/10.1142/S021962201240007X.
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    • Jiang, B., J. Pei, X. Lin, and Y. Yuan. “Probabilistic skylines on uncertain data: Model and bounding-pruning- refining methods.” Journal of Intelligent Information Systems 38, no. 1 (February 1, 2012): 1–39. https://doi.org/10.1007/s10844-010-0141-4.
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    • Zhou, B., and J. Pei. “Aggregate keyword search on large relational databases.” Knowledge and Information Systems 30, no. 2 (February 1, 2012): 283–318. https://doi.org/10.1007/s10115-011-0379-3.
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    • Han, J. W., M. Kamber, and J. Pei. “Clustering analysis.” Data Mining: Concept and Technique, Mk Imprint of Elsevier, New York, 2012, 478–90.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Classification: advanced methods.” Data Mining Concepts and Techniques, 2012, 393–443.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “6-mining frequent patterns, associations, and correlations: Basic concepts and methods.” Data Mining: Concepts and Techniques, 2012, 243–78.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Outlier detection.” Data Mining: Concepts and Techniques, 2012, 543–84.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data mining: concepts and techniques, Waltham, MA.” Morgan Kaufman Publishers 10 (2012): 978–1.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data mining: Data mining concepts and techniques.” Data Min Concepts Tech 3 (2012): 740–740.
    • Jiang, Q., A. Campbell, G. Tang, and J. Pei. “Multi-level relationship outlier detection.” International Journal of Business Intelligence and Data Mining 7, no. 4 (January 1, 2012): 253–73. https://doi.org/10.1504/IJBIDM.2012.051713.
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    • Kamber, Jiawei Han Micheline, Jian Pei Jiawei Han, Micheline Kamber, and Jian Pei. “Outlier Detection,” 2012.
    • Mclachlan, Geoffrey, Jian Pei, Christos Faloutsos, G. Melli, F. Bonchi, R. Ghani, B. Goethals, et al. “Top-10 Data Mining Case Studies,” 2012.
    • Pei, Jian, and Pete Barnum. “COMP5331: Knowledge Discovery and Data Mining,” 2012.
    • Pei, Jian. “MSC BD 5002/IT 5210: Knowledge Discovery and Data Mining,” 2012.
    • Yang, Qiang, Deepak Agarwal, and Jian Pei. “Proceedings of the Data Mining and Intelligent Knowledge Management Workshop,” 2012.
    • Sun, X., H. Wang, J. Li, and J. Pei. “Publishing anonymous survey rating data.” Data Mining and Knowledge Discovery 23, no. 3 (November 1, 2011): 379–406. https://doi.org/10.1007/s10618-010-0208-4.
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    • Liao, Z., D. Jiang, E. Chen, J. Pei, H. Cao, and H. Li. “Mining concept sequences from large-scale search logs for context-aware query suggestion.” Acm Transactions on Intelligent Systems and Technology 3, no. 1 (October 1, 2011). https://doi.org/10.1145/2036264.2036281.
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    • Wong, R. C. W., A. W. C. Fu, K. Wang, P. S. Yu, and J. Pei. “Can the utility of anonymized data be used for privacy breaches?” Acm Transactions on Knowledge Discovery From Data 5, no. 3 (August 1, 2011). https://doi.org/10.1145/1993077.1993080.
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    • Zhang, Y., W. Zhang, X. Lin, B. Jiang, and J. Pei. “Ranking uncertain sky: The probabilistic top-k skyline operator.” Information Systems 36, no. 5 (July 1, 2011): 898–915. https://doi.org/10.1016/j.is.2011.03.008.
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    • Hua, M., J. Pei, and X. Lin. “Ranking queries on uncertain data.” Vldb Journal 20, no. 1 (February 1, 2011): 129–53. https://doi.org/10.1007/s00778-010-0196-4.
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    • Hua, Ming, Jian Pei, and Xuemin Lin. “Ranking queries on uncertain data.” The Vldb Journal 20 (2011): 129–53.
    • Liu, Yunhao, Yiyang Zhao, Lei Chen, Jian Pei, and Jinsong Han. “Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays.” Ieee Transactions on Parallel and Distributed Systems 23 (2011): 2138–49.
    • Pei, J., J. Gama, Q. Yang, R. Huang, and X. Li. “Best papers from the Fifth International Conference on Advanced Data Mining and Applications (ADMA 2009).” Knowledge and Information Systems 27, no. 2 (January 1, 2011): 163–64. https://doi.org/10.1007/s10115-011-0399-z.
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    • Pei, Jian. “Early Classification: Problems.” Preliminary Results, and Opportunities, 2011.
    • Zhou, B., and J. Pei. “The k-anonymity and l-diversity approaches for privacy preservation in social networks against neighborhood attacks.” Knowledge and Information Systems 28, no. 1 (January 1, 2011): 47–77. https://doi.org/10.1007/s10115-010-0311-2.
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    • Goethals, B., and J. Pei. “Special issue on the best papers of SDM'10.” Statistical Analysis and Data Mining 3, no. 6 (December 1, 2010): 359–60. https://doi.org/10.1002/sam.10094.
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    • Lin, Z., B. Jiang, J. Pei, and D. Jiang. “Mining discriminative items in multiple data streams.” World Wide Web 13, no. 4 (July 12, 2010): 497–522. https://doi.org/10.1007/s11280-010-0094-0.
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    • Xing, Z., and J. Pei. “Exploring disease association from the NHANES data: Data mining, pattern summarization, and visual analytics.” International Journal of Data Warehousing and Mining 6, no. 3 (July 1, 2010): 11–27. https://doi.org/10.4018/jdwm.2010070102.
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    • Yuen, S. M., Y. Tao, X. Xiao, J. Pei, and D. Zhang. “Superseding nearest neighbor search on uncertain spatial databases.” Ieee Transactions on Knowledge and Data Engineering 22, no. 7 (June 4, 2010): 1041–55. https://doi.org/10.1109/TKDE.2009.137.
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    • Huang, J., F. Zhao, J. Chen, J. Pei, and J. Yin. “Towards progressive and load balancing distributed computation: A case study on skyline analysis.” Journal of Computer Science and Technology 25, no. 3 (May 1, 2010): 431–43. https://doi.org/10.1007/s11390-010-9335-z.
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    • Aljaber, B., N. Stokes, J. Bailey, and J. Pei. “Document clustering of scientific texts using citation contexts.” Information Retrieval 13, no. 2 (April 1, 2010): 101–31. https://doi.org/10.1007/s10791-009-9108-x.
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    • Cheema, M. A., X. Lin, W. Wang, W. Zhang, and J. Pei. “Probabilistic reverse nearest neighbor queries on uncertain data.” Ieee Transactions on Knowledge and Data Engineering 22, no. 4 (April 1, 2010): 550–64. https://doi.org/10.1109/TKDE.2009.108.
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    • Loekito, E., J. Bailey, and J. Pei. “A binary decision diagram based approach for mining frequent subsequences.” Knowledge and Information Systems 24, no. 2 (January 1, 2010): 235–68. https://doi.org/10.1007/s10115-009-0252-9.
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    • Parthasarathy, Srinivasan, Bing Liu, Bart Goethals, Jian Pei, and Chandrika Kamath. “10th SIAM International Conference on Data Mining 2010,” 2010.
    • Pei, Jian, Lise Getoor, and Ander de Keijzer. “Summary of the first ACM SIGKDD workshop on knowledge discovery from uncertain data (U’09).” Acm Sigkdd Explorations Newsletter 11 (2010): 90–91.
    • Pei, Jian. “Outlier Detection,” 2010.
    • Raïssi, C., J. Pei, and T. Kister. “Computing closed skycubes.” Proceedings of the Vldb Endowment 3, no. 1 (January 1, 2010): 838–47. https://doi.org/10.14778/1920841.1920948.
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    • Xing, Zhengzheng, Jian Pei, and Eamonn Keogh. “A brief survey on sequence classification.” Acm Sigkdd Explorations Newsletter 12 (2010): 40–48.
    • Zhang, W., X. Lin, Y. Zhang, J. Pei, and W. Wang. “Threshold-based probabilistic top-k dominating queries.” Vldb Journal 19, no. 2 (January 1, 2010): 283–305. https://doi.org/10.1007/s00778-009-0162-1.
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    • Hua, M., and J. Pei. “Continuously monitoring top-k uncertain data streams: a probabilistic threshold method.” Distributed and Parallel Databases 26, no. 1 (August 1, 2009): 29–65. https://doi.org/10.1007/s10619-009-7043-x.
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    • Zhou, B., and J. Pei. “Link spam target detection using page farms.” Acm Transactions on Knowledge Discovery From Data 3, no. 3 (July 1, 2009). https://doi.org/10.1145/1552303.1552306.
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    • Hua, M., J. Pei, A. W. C. Fu, X. Lin, and H. F. Leung. “Top-k typicality queries and efficient query answering methods on large databases.” Vldb Journal 18, no. 3 (June 1, 2009): 809–35. https://doi.org/10.1007/s00778-008-0128-8.
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    • Ng, Man-Ping, Ismael A. Vergara, Christian Frech, Qingkang Chen, Xinghuo Zeng, Jian Pei, and Nansheng Chen. “OrthoClusterDB: an online platform for synteny blocks.” Bmc Bioinformatics 10 (June 2009): 192. https://doi.org/10.1186/1471-2105-10-192.
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    • Wong, R. C. W., A. W. C. Fu, K. Wang, and J. Pei. “Anonymization-based attacks in privacy-preserving data publishing.” Acm Transactions on Database Systems 34, no. 2 (June 1, 2009). https://doi.org/10.1145/1538909.1538910.
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    • Chi-Wing Wong, Raymond, Ada Wai-Chee Fu, Ke Wang, Yabo Xu, Jian Pei, and Philip S. Yu. “Anonymization with Worst-Case Distribution-Based Background Knowledge.” Arxiv E Prints, 2009, arXiv-0909.
    • Hua, M., M. K. Lau, J. Pei, and K. Wu. “Continuous K-means monitoring with low reporting cost in sensor networks.” Ieee Transactions on Knowledge and Data Engineering 21, no. 12 (January 1, 2009): 1679–91. https://doi.org/10.1109/TKDE.2009.41.
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    • Jiang, D., and J. Pei. “Mining frequent cross-graph quasi-cliques.” Acm Transactions on Knowledge Discovery From Data 2, no. 4 (January 1, 2009). https://doi.org/10.1145/1460797.1460799.
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    • Ng, Man-Ping, Ismael A. Vergara, Christian Frech, Qingkang Chen, Xinghuo Zeng, Jian Pei, and Nansheng Chen. “OrthoClusterDB: an online platform for synteny blocks.” Bmc Bioinformatics 10 (2009): 1–8.
    • She, Rong, Jeffrey S-C Chu, Ke Wang, Jian Pei, and Nansheng Chen. “GenBlastA: enabling BLAST to identify homologous gene sequences.” Genome Research 19, no. 1 (January 2009): 143–49. https://doi.org/10.1101/gr.082081.108.
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    • Wong, R. C. W., J. Pei, A. W. C. Fu, and K. Wang. “Online skyline analysis with dynamic preferences on nominal attributes.” Ieee Transactions on Knowledge and Data Engineering 21, no. 1 (January 1, 2009): 35–49. https://doi.org/10.1109/TKDE.2008.115.
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    • Wong, Raymond Chi-Wing, Ada Wai-Chee Fu, Ke Wang, Yabo Xu, Jian Pei, and Philip S. Yu. “Anonymization with Worst-Case Distribution-Based Background Knowledge.” Arxiv Preprint Arxiv:0909.1127, 2009.
    • Zeng, X., J. Pei, K. Wang, and J. Li. “PADS: A simple yet effective pattern-aware dynamic search method for fast maximal frequent pattern mining.” Knowledge and Information Systems 20, no. 3 (January 1, 2009): 375–91. https://doi.org/10.1007/s10115-008-0179-6.
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    • Li, J., R. C. W. Wong, A. W. C. Fu, and J. Pei. “Anonymization by local recoding in data with attribute hierarchical taxonomies.” Ieee Transactions on Knowledge and Data Engineering 20, no. 9 (September 1, 2008): 1181–94. https://doi.org/10.1109/TKDE.2008.52.
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    • Wang, H., and J. Pei. “Clustering by pattern similarity.” Journal of Computer Science and Technology 23, no. 4 (July 1, 2008): 481–96. https://doi.org/10.1007/s11390-008-9148-5.
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    • Wang, Haixun, and Jian Pei. “??” ????????? 23 (2008): 481–96.
    • Wong, R. C. W., A. W. C. Fu, J. Pei, Y. S. Ho, T. Wong, and Y. Liu. “Efficient skyline querying with variable user preferences on nominal attributes.” Proceedings of the Vldb Endowment 1, no. 1 (January 1, 2008): 1032–43. https://doi.org/10.14778/1453856.1453967.
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    • Zhou, Bin, Jian Pei, and WoShun Luk. “A brief survey on anonymization techniques for privacy preserving publishing of social network data.” Acm Sigkdd Explorations Newsletter 10 (2008): 12–22.
    • Tao, Y., K. Xiao, and J. Pei. “Efficient skyline and top-k retrieval in subspaces.” Ieee Transactions on Knowledge and Data Engineering 19, no. 8 (August 1, 2007): 1072–88. https://doi.org/10.1109/TKDE.2007.1051.
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    • Liu, C., K. Wu, and J. Pei. “An energy-efficient data collection framework for wireless sensor networks by exploiting spatiotemporal correlation.” Ieee Transactions on Parallel and Distributed Systems 18, no. 7 (July 1, 2007): 1010–23. https://doi.org/10.1109/TPDS.2007.1046.
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    • Pei, J., J. Han, H. Lu, S. Nishio, S. Tang, and D. Yang. “H-Mine: Fast and space-preserving frequent pattern mining in a large databases.” Iie Transactions (Institute of Industrial Engineers) 39, no. 6 (June 1, 2007): 593–605. https://doi.org/10.1080/07408170600897460.
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    • Pei, J., J. Han, and W. Wang. “Constraint-based sequential pattern mining: The pattern-growth methods.” Journal of Intelligent Information Systems 28, no. 2 (April 1, 2007): 133–60. https://doi.org/10.1007/s10844-006-0006-z.
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    • Chi-Wing Wong, Raymond, Wai-chee Fu, Jian Pei, Yip Sing Ho, Tai Wong, Yubao Liu, and Yubao others. “Efficient Skyline Querying with Variable User Preferences on Nominal Attributes.” Arxiv E Prints, 2007, arXiv-0710.
    • Cho, M., J. Pei, and K. Wang. “Answering ad hoc aggregate queries from data streams using prefix aggregate trees.” Knowledge and Information Systems 12, no. 3 (January 1, 2007): 301–29. https://doi.org/10.1007/s10115-006-0024-8.
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    • Jiang, D., J. Pei, M. Ramanathan, C. Lin, C. Tang, and A. Zhang. “Mining gene-sample-time microarray data: A coherent gene cluster discovery approach.” Knowledge and Information Systems 13, no. 3 (January 1, 2007): 305–35. https://doi.org/10.1007/s10115-006-0031-9.
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    • Ng, Raymond T., and Jian Pei. “Introduction to the special issue on data mining for health informatics.” Acm Sigkdd Explorations Newsletter 9 (2007): 1–2.
    • Varde, Aparna, Jian Pei, and Jian others. “Proceedings of the ACM first Ph. D. Workshop in CIKM,” 2007.
    • Wong, Raymond Chi-Wing, Ada Wai-Chee Fu, Jian Pei, Yip Sing Ho, Tai Wong, and Yubao Liu. “Efficient skyline querying with variable user preferences on nominal attributes.” Arxiv Preprint Arxiv:0710.2604, 2007.
    • Chen, Y., G. Dong, J. Han, J. Pei, B. W. Wah, and J. Wang. “Regression cubes with lossless compression and aggregation.” Ieee Transactions on Knowledge and Data Engineering 18, no. 12 (December 1, 2006): 1585–98. https://doi.org/10.1109/TKDE.2006.196.
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    • Huang, Y., J. Pei, and H. Xiong. “Mining co-location patterns with rare events from spatial data sets.” Geoinformatica 10, no. 3 (September 1, 2006): 239–60. https://doi.org/10.1007/s10707-006-9827-8.
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    • Wang, J., J. Han, and J. Pei. “Closed constrained gradient mining in retail databases.” Ieee Transactions on Knowledge and Data Engineering 18, no. 6 (June 1, 2006): 764–69. https://doi.org/10.1109/TKDE.2006.88.
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    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data mining: concepts and techniques Morgan Kaufmann.” San Francisco, 2006.
    • Pei, J., J. Han, and L. V. S. Lakshmanan. “Erratum: Pushing convertible constraints in frequent itemset mining (Data Mining and Knowledge Discovery: An International Journal (May 2004) 8:3 (227-252)).” Data Mining and Knowledge Discovery 12, no. 1 (January 1, 2006): 119. https://doi.org/10.1007/s10618-005-0022-6.
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    • Pei, J., P. S. Yu, and K. Wang. “Discovering frequent closed partial orders from strings.” Ieee Transactions on Knowledge and Data Engineering 18, no. 11 (January 1, 2006): 1467–81. https://doi.org/10.1109/TKDE.2006.172.
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    • Pei, Jian, Jiawei Han, and Laks V. S. Lakshmanan. “An Erratum on" Pushing Convertible Constraints in Frequent Itemset Mining".” Data Min. Knowl. Discov. 12 (2006): 119–119.
    • Pei, Jian, Jiawei Han, and Laks V. S. Lakshmanan. “An Erratum on" Pushing Convertible Constraints in Frequent Itemset Mining".” Data Min. Knowl. Discov. 12 (2006): 119–119.
    • Wong, Raymond Chi-Wing, Ada Wai-Chee Fu, Jian Pei, Ke Wang, Steven Chi-Wen Wan, and C. S. Lo. “Multidimensional k-anonymization by linear clustering using space-filling curves.” Simon Fraser University School of Computing Science Technical Report, 2006.
    • Xu, Jian, Wei Wang, Jian Pei, Xiaoyuan Wang, Baile Shi, and Ada Wai-Chee Fu. “Utility-based anonymization for privacy preservation with less information loss.” Acm Sigkdd Explorations Newsletter 8 (2006): 21–30.
    • Jiang, D., J. Pei, and A. Zhang. “An interactive approach to mining gene expression data.” Ieee Transactions on Knowledge and Data Engineering 17, no. 10 (October 1, 2005): 1363–78. https://doi.org/10.1109/TKDE.2005.159.
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    • Han, J., Y. Chen, G. Dong, J. Pei, B. W. Wah, J. Wang, and Y. D. Cai. “Scream cube: An architecture for multi-dimensional analysis of data streams.” Distributed and Parallel Databases 18, no. 2 (September 1, 2005): 173–97. https://doi.org/10.1007/s10619-005-3296-1.
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    • Aggarwal, Charu C., and Jian Pei. “A Framework for Adversarial Privacy Preserving Data Mining.” Tr 2005–08, 2005.
    • Cho, M., J. Pei, H. Wang, and W. Wang. “Preference-Based Frequent Pattern Mining.” International Journal of Data Warehousing and Mining (Ijdwm) 1, no. 4 (January 1, 2005): 56–77. https://doi.org/10.4018/jdwm.2005100103.
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    • Han, Jiawei, Yixin Chen, Guozhu Dong, Jian Pei, Benjamin W. Wah, Jianyong Wang, and Y Dora Cai. “Stream cube: An architecture for multi-dimensional analysis of data streams.” Distributed and Parallel Databases 18 (2005): 173–97.
    • Pei, Jian, Wen Jin, Martin Ester, and Yufei Tao. “Catching the best views of skyline: A semantic approach based on decisive subspaces.” Space (X, Y) 100 (2005): 1–1.
    • Deng, L., J. Ma, and J. Pei. “Rank sum method for related gene selection and its application to tumor diagnosis.” Chinese Science Bulletin 49, no. 15 (December 1, 2004): 1652–57. https://doi.org/10.1360/03we0143.
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    • Pei, J., J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, and M. C. Hsu. “Mining sequential patterns by pattern-growth: The prefixspan approach.” Ieee Transactions on Knowledge and Data Engineering 16, no. 11 (November 1, 2004): 1424–40. https://doi.org/10.1109/TKDE.2004.77.
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    • Dong, G., J. Han, J. M. W. Lam, J. Pei, K. Wang, and W. Zou. “Mining constrained gradients in large databases.” Ieee Transactions on Knowledge and Data Engineering 16, no. 8 (August 1, 2004): 922–38. https://doi.org/10.1109/TKDE.2004.28.
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    • Pei, J., J. Han, and L. V. S. Lakshmanan. “Pushing convertible constraints in frequent itemset mining.” Data Mining and Knowledge Discovery 8, no. 3 (May 1, 2004): 227–52. https://doi.org/10.1023/B:DAMI.0000023674.74932.4c.
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    • Han, J. W., J. Pei, and X. F. Yan. “From sequential pattern mining to structured pattern mining: A pattern-growth approach.” Journal of Computer Science and Technology 19, no. 3 (January 1, 2004): 257–79. https://doi.org/10.1007/BF02944897.
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    • Han, J., J. Pei, Y. Yin, and R. Mao. “Mining frequent patterns without candidate generation: A frequent-pattern tree approach.” Data Mining and Knowledge Discovery 8, no. 1 (January 1, 2004): 53–87. https://doi.org/10.1023/B:DAMI.0000005258.31418.83.
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    • Han, Jiawei, and Micheline Kamber. “Adatbányászat.” Koncepciók És Technikák Panem Könyvkiadó, Budapest, 2004.
    • Pei, Jian, Guozhu Dong, Wei Zou, and Jiawei Han. “Mining condensed frequent-pattern bases.” Knowledge and Information Systems 6 (2004): 570–94.
    • Yang, Dongqing, Shiwei Tang, Jian Pei, Tengjiao Wang, and Jun Gao. “First International Workshop on Conceptual Model-Directed Web Information Integration and Mining (CoMWIM 2004)-Preface to CoMWIM 2004.” Lecture Notes in Computer Science 3289 (2004): 197–197.
    • Chen, Z., C. Li, J. Pei, Y. Tao, H. Wang, W. Wang, J. Yang, and D. Zhang. “Recent Progress on Selected Topics in Database Research - A Report by Nine Young Chinese Researchers Working in the United States.” Journal of Computer Science and Technology 18, no. 5 (January 1, 2003): 538–52. https://doi.org/10.1007/bf02947114.
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    • Chen, Zhiyuan, Li Chen, Jian Pei, Yufei Tao, Haixun Wang, Wei Wang, Jiong Yang, Jun Yang, and Donghui Zhang. “Recent Progress on Selected Topics in Database Research - A Report by Nine Young Chinese Researchers Working in the United States.” J. Comput. Sci. Technol. 18 (2003): 538–52.
    • Giannella, Chris, Jiawei Han, Jian Pei, Xifeng Yan, and Philip S. Yu. “Mining frequent patterns in data streams at multiple time granularities.” Next Generation Data Mining 212 (2003): 191–212.
    • Jiajia, Ma, Ma Heng, Wang Yuemin, Li Hongmei, and Pei Jianming. “Vasodilation effect of puerarin on abdominal aortic artery in the rat and the underlying mechanism.” Journal of the Fourth Military Medical University 24 (2003): 2231–34.
    • Jiang, Daxin, Jian Pei, and Aidong Zhang. “Towards interactive exploration of gene expression patterns.” Acm Sigkdd Explorations Newsletter 5 (2003): 79–90.
    • Pei, J. “A general model for online analytical processing of complex data.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2813 (January 1, 2003): 321–34. https://doi.org/10.1007/978-3-540-39648-2_26.
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    • Chen, Yixin, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, and Jianyong Wang. “Online Analytical Processing Stream: Is it Feasible?,” 2002.
    • Pei, Jian, and Jiawei Han. “Constrained frequent pattern mining: a pattern-growth view.” Acm Sigkdd Explorations Newsletter 4 (2002): 31–39.
    • Han, J., J. Pei, G. Dong, and K. Wang. “Efficient computation of iceberg cubes with complex measures.” Sigmod Record (Acm Special Interest Group on Management of Data) 30, no. 2 (January 1, 2001): 1–12. https://doi.org/10.1145/376284.375664.
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    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data mining: concepts and technologies.” Data Mining Concepts Models Methods & Algorithms 5 (2001): 1–18.
    • Hau, J., Y. Lu, Y. Liao, J. Pei, H. Jamil, and L. Chen. “DNA-Miner: A System Prototype for Mining DNA Sequences.” Sigmod Record 30, no. 2 (January 1, 2001): 618. https://doi.org/10.1145/376284.375786.
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    • Pei, J., J. Han, and L. V. S. Lakshmanan. “Mining frequent itemsets with convertible constraints.” Proceedings  International Conference on Data Engineering, January 1, 2001, 433–42. https://doi.org/10.1109/ICDE.2001.914856.
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    • Pei, Jian, Anthony K. H. Tung, and Jiawei Han. “Fault-Tolerant Frequent Pattern Mining: Problems and Challenges.” Dmkd 1 (2001): 270–270.
    • Han, J., J. Pei, and Y. Yin. “Mining frequent patterns without candidate generation.” Sigmod Record (Acm Special Interest Group on Management of Data) 29, no. 2 (January 1, 2000): 1–12. https://doi.org/10.1145/335191.335372.
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    • Han, Jiawei, and Jian Pei. “Mining frequent patterns by pattern-growth: methodology and implications.” Acm Sigkdd Explorations Newsletter 2 (2000): 14–20.
    • Han, Jiawei. “Frequent pattern-projected sequential pattern mining.” Proc. of the Acm Sigkdd, 2000, 2000.
    • Pei, J., R. Mao, K. Hu, and H. Zhu. “Tow ards Data Mining Benchmarking: A Test Bed for Performance Study of Frequent Pattern Mining.” Sigmod Record 29, no. 2 (January 1, 2000): 592. https://doi.org/10.1145/335191.336572.
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    • Pei, J., W. Chai, C. Zhao, S. Tang, and D. Yang. “Algebra for online analytical processing data cube.” Acta Metallurgica Sinica (English Letters) 12, no. 5 (October 1, 1999): 561–69.
    • Tang, Chun, Aidong Zhang, and Jian Pei. “Genes,” 1997.
    • Pei, Zhaohui, Jingzao Chen, Miaozhang Zhu, Jianming Pei, Zhaohui Liu, and Yongxia Tan. “Plasma levels of endothelin-1, nitric oxide, malondialdehyde and superoxide dismutase in rats exposed to infrasound.” Chinese Journal of Pathophysiology, 1986.
    • Bailey, Bader Aljaber Nicola Stokes James, and Jian Pei. “Document Clustering of Scientific Texts Using Citation Contexts,” n.d.
    • Bailey, James, Bettina Berendt, Longbing Cao, Australia Nitesh Chawla, Xueqi Chen, Jana Diesner, Wei Ding, et al. “Ulrik Brandes, University of Konstanz, Germany Piotr Br6dka, Wroc1aw University of Technology, Poland Yi Cai, South China University of Technology, China,” n.d.
    • Bonchi, Francesco, Longbing Cao, Ming-Syan Chen, Diane J. Cook, Eric Gaussier, Bart Goethals, Geun-Sik Jo, et al. “DSAA 2019,” n.d.
    • Bonchi, Francesco, Longbing Cao, Ming-Syan Chen, Diane J. Cook, Eric Gaussier, Bart Goethals, Geun-Sik Jo, et al. “Steering Committee DSAA 2020,” n.d.
    • Cercone, Nick, Xueqi Cheng, Xiaohua Hu, Raghunath Nambiar, Jian Pei, Vijay Raghavan, Amit Sheth, et al. “Big Data Steering Committee,” n.d.
    • Chakrabarti, Deepayan, Ed Chang, Olivier Chapelle, Chris Clifton, Brian Davison, Chris Ding, Martin Ester, et al. “SIGKDD-2010 Program Committees,” n.d.
    • Chen, Jinjun, Laurence T. Yang, Ramamohanarao Kotagiri, Jian Pei, Xian-He Sun, Sartaj Sahni, Stan Matwin, Zhaohui Wu, Manish Parashar, and Albert Zomaya. “DSS 2017,” n.d.
    • Chen, Yixin, Guozhu Dong, Jian Pei, Benjamin W. Wah, and Jianyong Wang. “Stream C ube: A n A rchitecture for,” n.d.
    • Chomicki, Jan, Jian Pei, Rohini K. Srihari, Guizhen Yang, and Aidong Zhang. “Database Research at University at Buffalo,” n.d.
    • Cook, Diane, Jian Pei, Wei Wang, Osmar Zaïane, and Xindong Wu. “11th IEEE International Conference on Data Mining,” n.d.
    • Crago, Stephen, Schahram Dustdar, Ian Foster, Geoffrey Fox, Minyi Guo, Francisco Herrera, Runhe Huang, et al. “BigDataSE 2021,” n.d.
    • Cui, Jianwei, Jian Pei, and Jo ao Gama. “The International Conference on Advanced Data Mining And Application ADMA2009,” n.d.
    • Fox, Geoffrey Charles, Xian-He Sun, Jian Pei, Xuyun Zhang, Xiaolin Li, Jinjun Chen, Aleksandar Stupar, et al. “BigDataMR2012 Organizing and Program Committees,” n.d.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “4 Major Tasks in Data Preprocessing,” n.d.
    • Huang, Feihu, Shangqian Gao, Jian Pei, and Heng Huang. “Momentum-Based Policy Gradient Methods Download PDF,” n.d.
    • Huang, Feihu, Shangqian Gao, Jian Pei, and Heng Huang. “Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization Download PDF,” n.d.
    • Jamil, Hasan, Jian Pei, and Alfredo Cuzzocrea. “Session details: Artificial intelligence & agents, information systems, and software development: Data mining track,” n.d.
    • Jiang, Bin, Jian Pei, Xuemin Lin, David W. Cheung, and Jiawei Han. “Mining Preferences from Superior and Inferior Examples TR 2008-09,” n.d.
    • Kumar, Ravi, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, and Xindong Wu. “ICDM 2014 14th IEEE International Conference on Data Mining Shenzhen, China/14-17 December 2014,” n.d.
    • Kung, Sun-Yuan, Albert Zomaya, Meikang Qiu, Zheng Yan, Yulei Wu, Jinjun Chen, Laurence T. Yang, et al. “Committee Members BigDataSE 2018,” n.d.
    • Liao, Zhen, Daxin Jiang, Jian Pei, Dongyeop Kang, Xiaohui Sun, Ho-Jin Choi, and Hang Li. “Constructing a Multidimensional Topic-Concept Cube for OLAP on Large-Scale Search Logs,” n.d.
    • Pei, Jian, Bin Zhou, Zhaohui Tang, and Dylan Huang. “Data Mining Techniques for Web Spam Detection.” Simon Fras University Microsoft Ad Center, n.d.
    • Pei, Jian, Ming Hua, Yufei Tao, and Xuemin Lin. “Mining Uncertain and Probabilistic Data,” n.d.
    • Pei, Jian, S. R. Ariwala, and Daxin Jiang. “Online mining changes of clusters in data streams.” Submitted for Publication, n.d.
    • Pei, Jian, Shambhu J. Upadhyaya, Faisal Farooq, and Venugopal Govindaraju. “Data Mining for Intrusion Detection,” n.d.
    • Pei, Jian, and Hui Xiong. “Mining Co-location Patterns with Rare Events from Spatial Data Sets* Yan Huang (huangyan@ unt. edu) Dept. of Computer Science and Engineering, University of North Texas, USA,” n.d.
    • Pei, Jian, and Ke Wang. “Online Skyline Analysis with Dynamic Preferences on Nominal Attributes,” n.d.
    • Pei, Jian. “The Pattern-based Approaches to Mining Microarray Data,” n.d.
    • Pei, Jian. “SPOTLIGHT ON TRANSACTIONS,” n.d.
    • Pei, Jian. “Towards Trustworthy Data Science: Interpretability, Fairness and Marketplaces,” n.d.
    • Steinbach, Michael, Vipin Kumar, Jiawei Han, Micheline Kamber, and Jian Pei. “MSCIT 5210: Knowledge Discovery and Data Mining,” n.d.
    • Tao, Yufei, Jian Li, Ling Ding, Xuemin Lin, and Jian Pei. “On Representing Skylines by Distance,” n.d.
    • Wang, Haixin, Cheng Xu, Ce Zhang, Jianliang Xu, Zhe Peng, and Jian Pei. “vChain+: Optimizing Verifiable Blockchain Boolean Range Queries,” n.d.
    • Wong, Raymond Chi-Wing, Ada Wai-Chee Fu, Jian Pei, Ke Wang, Steven Chi-Wen Wan, and C. S. Lo. “Multidimensional k-Anonymization by Linear Clustering Using Space-Filling Curves Technical Report TR 2006-27,” n.d.
    • Wong, Raymond Chi-Wing, Ada Wai-Chee Fu, Ke Wang, and Jian Pei. “Minimality Attack in Privacy Preserving Data Publishing Technical Report TR 2006-28,” n.d.
    • Xing, Zhengzheng, and Jian Pei. “Running Title: Exploring Disease Association from the NHANES Data,” n.d.
    • Xu, Yabo, Ke Wang, Ada Wai-Chee Fu, Rong She, and Jian Pei. “Privacy-Preserving Classification for Data Streams,” n.d.
    • Yang, Yu, Xiangbo Mao, Jian Pei, and Xiaofei He. “Continuous Influence Maximization: Algorithmic Framework and Implementation under Triggering Models,” n.d.
    • Zhou, Zhi-Hua, Wei Wang, Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, and Xindong Wu. “ICDMW 2014 14th IEEE International Conference on Data Mining Workshops Shenzhen, China/14 December 2014,” n.d.

  • Book Sections

    • Cui, Peng, Lingfei Wu, Jian Pei, Liang Zhao, and Xiao Wang. “Graph Representation Learning.” In Graph Neural Networks: Foundations, Frontiers, and Applications, 17–26. Springer, Singapore, 2022.
    • Wu, Lingfei, Peng Cui, Jian Pei, Liang Zhao, and Le Song. “Graph neural networks.” In Graph Neural Networks: Foundations, Frontiers, and Applications, 27–37. Springer, Singapore, 2022.
    • Zhao, Liang, Lingfei Wu, Peng Cui, and Jian Pei. “Representation Learning.” In Graph Neural Networks: Foundations, Frontiers, and Applications, 3–15. Springer, Singapore, 2022.
    • Liu, J., L. Xiong, J. Pei, J. Luo, and H. Zhang. “Finding pareto optimal groups: Group-based skyline.” In Proceedings of the VLDB Endowment, 8:2086–97, 2015. https://doi.org/10.14778/2831360.2831363.
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    • Han, J., and J. Pei. “Pattern-growth methods.” In Frequent Pattern Mining, 9783319078212:65–81, 2014. https://doi.org/10.1007/978-3-319-07821-2_3.
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    • Hua, Ming, and Jian Pei. “Ranking Queries on Probabilistic Linkages.” In Ranking Queries on Uncertain Data, 151–84. Springer, New York, NY, 2011.
    • Hua, Ming, and Jian Pei. “Top-k Typicality Queries on Uncertain Data.” In Ranking Queries on Uncertain Data, 51–87. Springer, New York, NY, 2011.
    • Hua, Ming, and Jian Pei. “Probabilistic Ranking Queries on Uncertain Data.” In Ranking Queries on Uncertain Data, 89–128. Springer, New York, NY, 2011.
    • Hua, Ming, and Jian Pei. “Continuous Ranking Queries on Uncertain Streams.” In Ranking Queries on Uncertain Data, 129–50. Springer, New York, NY, 2011.
    • Pei, J., X. Zhang, M. Cho, H. Wang, and P. S. Yu. “On mining maximal pattern-based clusters.” In Data Mining for Business Applications, 31–52, 2009. https://doi.org/10.1007/978-0-387-79420-4_3.
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    • Hua, Ming, and Jian Pei. “A survey of utility-based privacy-preserving data transformation methods.” In Privacy-Preserving Data Mining, 207–37. Springer, Boston, MA, 2008.
    • Xu, Yabo, Ke Wang, Ada Wai-Chee Fu, Rong She, and Jian Pei. “Privacy-preserving data stream classification.” In Privacy-Preserving Data Mining, 487–510. Springer, Boston, MA, 2008.
    • Xu, Yabo, Ke Wang, Ada Wai-Chee Fu, Rong She, and Jian Pei. “Privacy-preserving data stream classification.” In Privacy-Preserving Data Mining, 487–510. Springer, Boston, MA, 2008.
    • Chen, L., J. Zeng, and J. Pei. “Classifying noisy and incomplete medical data by a differential latent semantic indexing approach.” In Springer Optimization and Its Applications, 7:169–76, 2007. https://doi.org/10.1007/978-0-387-69319-4_10.
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    • Dong, Guozhu, and Jian Pei. “Classification, clustering, features and distances of sequence data.” In Sequence Data Mining, 47–65. Springer, Boston, MA, 2007.
    • Dong, Guozhu, and Jian Pei. “Mining partial orders from sequences.” In Sequence Data Mining, 89–112. Springer, Boston, MA, 2007.
    • Dong, Guozhu, and Jian Pei. “Frequent and closed sequence patterns.” In Sequence Data Mining, 15–46. Springer, Boston, MA, 2007.
    • Dong, Guozhu, and Jian Pei. “Sequence Motifs: Identifying and Characterizing Sequence Families.” In Sequence Data Mining, 67–87. Springer, Boston, MA, 2007.
    • Dong, Guozhu, and Jian Pei. “Distinguishing Sequence Patterns.” In Sequence Data Mining, 113–30. Springer, Boston, MA, 2007.
    • Han, Jiawei, Y Dora Cai, Yixin Chen, Guozhu Dong, Jian Pei, Benjamin W. Wah, and Jianyong Wang. “Multi-dimensional analysis of data streams using stream cubes.” In Data Streams, 103–25. Springer, Boston, MA, 2007.
    • Han, Jiawei, Jian Pei, and Xifeng Yan. “Sequential pattern mining by pattern-growth: Principles and extensions.” In Foundations and Advances in Data Mining, 183–220. Springer, Berlin, Heidelberg, 2005.
    • Jiang, D., A. Zhang, and J. Pei. “GPX.” In Proceedings 2004 VLDB Conference: The 30th International Conference on Very Large Databases (VLDB), 1249–52, 2004. https://doi.org/10.1016/B978-012088469-8.50119-4.
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    • Lakshmanan, L. V. S., J. Pei, and Y. Zhao. “Efficacious Data Cube Exploration by Semantic Summarization and Compression.” In Proceedings 2003 VLDB Conference: 29th International Conference on Very Large Databases (VLDB), 1125–28, 2003. https://doi.org/10.1016/B978-012722442-8/50121-X.
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  • Other Articles

    • Amer-Yahia, Sihem, and Jian Pei. “LETTER FROM THE PROGRAM CHAIRS.” Proceedings of the Vldb Endowment. ASSOC COMPUTING MACHINERY 2 PENN PLAZA, STE 701, NEW YORK, NY 10121-0701 USA, 2018.
    • Dolatshah, Mohamad, Mathew Teoh, Jiannan Wang, and Jian Pei. “Cleaning Crowdsourced Labels Using Oracles For Supervised Learning,” 2018.
    • Pei, Jian, Yannis Manolopoulos, Shazia Sadiq, and Jianxin Li. “Database Systems for Advanced Applications: 23rd International Conference, DASFAA 2018, Gold Coast, QLD, Australia, May 21-24, 2018, Proceedings, Part II.” Springer, 2018.
    • Pei, Jian, Fabrizio Silvestri, and Jie Tang. “Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015.” ACM, 2015.
    • Agarwal, Deepak, Rich Caruana, Jian Pei, and Ke Wang. “Introduction to the Special Issue ACM SIGKDD 2012.” Acm Transactions on Knowledge Discovery From Data (Tkdd). ACM New York, NY, USA, 2013.
    • Li, Jiuyong, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, and Vincent S. Tseng. “Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2013 Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Golden Coast, QLD, Australia, Revised Selected Papers.” Springer, 2013.
    • Fan, W. “Web-age information management.” Springer, Berlin, 2012.
    • Jiawei, Han, Micheline Kamber, J. Han, M. Kamber, and J. Pei. “Data Mining: Concepts and Techniques [Internet]. San Francisco, CA, itd.” Morgan Kaufmann, 2012.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data Mining: Concepts and Techniques [Internet]. Waltham.” Elsevier, 2011.
    • Jiawei Han, M. K., and Jian Pei. “Data mining: concepts and techniques: concepts and techniques.” Elsevier, Amsterdam, 2011.
    • Tsoukalas, Kathleen J., Jian Pei, and Davor Cubranic. “Systems and methods to automatically generate enhanced information associated with a selected web table,” August 5, 2010.
    • Arun, Rajkumar, V. Suresh, CE Veni Madhavan, MN Narasimha Murthy, M. J. Zaki, J. X. Yu, B. Ravindran, and V. Pudi. “Advances in knowledge discovery and data mining.” Berlin Heidelberg: Springer, 2010.
    • Parthasarathy, Srinivasan, Bing Liu, Bart Goethals, Jian Pei, and Chandrika Kamath. “Proceedings of the 2010 SIAM International Conference on Data Mining (SDM).” Society for Industrial and Applied Mathematics, 2010.
    • Shen, Heng Tao, Jian Pei, M Tamer Özsu, Lei Zou, Jiaheng Lu, Tok Wang Ling, Ge Yu, Yi Zhuang, and Jie Shao. “Web-Age Information Management. WAIM 2010 Workshops: WAIM 2010 International Workshops: IWGD 2010, WCMT 2010, XMLDM 2010, Jiuzhaigou Valley, China, July 15-17, 2010, Revised Selected Papers.” Springer Science & Business Media, 2010.
    • Shen, Heng Tao, Jian Pei, M Tamer Özsu, Lei Zou, Jiaheng Lu, Tok Wang Ling, Ge Yu, Yi Zhuang, and Jie Shao. “Web-Age Information Management. WAIM 2010 Workshops: WAIM 2010 International Workshops: IWGD 2010, WCMT 2010, XMLDM 2010, Jiuzhaigou Valley, China, July 15-17, 2010, Revised Selected Papers.” Springer Science & Business Media, 2010.
    • Huang, Hsiang-Cheh. “Information hiding and applications.” Springer, 2009.
    • Li, Qing, Ling Feng, Jian Pei, X Sean Wang, Xiaofang Zhou, and Qiaoming Zhu. “Advances in Data and Web Management: Joint International Conferences, APWeb/WAIM 2009, Suzhou, China, April 2-4, 2009, Proceedings.” Springer, 2009.
    • Pei, Jian, Lise Getoor, and Ander de Keijzer. “Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data.” ACM, 2009.
    • Dong, Guozhu, and Jian Pei. “Sequence data mining.” Springer Science & Business Media, 2007.
    • Han, Jiawei, Micheline Kamber, and Jian Pei. “Data preprocessing. Data mining: concepts and techniques.” San Francisco: Morgan Kaufmann, 2006.
    • Zhang, D., Y. Tong, S. Tang, and D. Yang. “Advanced Data Mining and Applications.” Springer Berlin, Germany:, 2005.
    • Han, Jiawei, Jian Pei, Yiwen Yin, and Runying Mao. “Methods and system for mining frequent patterns,” December 16, 2003.
    • Discovery, Pacific-Asia Conference on Knowledge, Data Mining, and Jian Pei. “Advances in knowledge discovery and data mining: 17th Pacific-Asia conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013: proceedings.” Springer, n.d.

  • Reports

    • Han, Jiawei, Jian Pei, and Yiwen Yin. “Mining partial periodicity using frequent pattern trees.” CS Tech. Rep. 99-10, Simon Fraser University, 1999.

  • Conference Papers

    • Peng, J., H. Zou, J. Liu, S. Li, Y. Jiang, J. Pei, and P. Cui. “Offline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping.” In Acm Web Conference 2023  Proceedings of the World Wide Web Conference, Www 2023, 1220–30, 2023. https://doi.org/10.1145/3543507.3583448.
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    • Kang, J., S. Zhang, B. Li, J. He, J. Pei, and D. Zhou. “TrustLOG: The First Workshop on Trustworthy Learning on Graphs.” In International Conference on Information and Knowledge Management, Proceedings, 5169–70, 2022. https://doi.org/10.1145/3511808.3557497.
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    • Wu, L., J. Pei, J. Tang, Y. Xia, and X. Guo. “Deep Learning on Graphs: Methods and Applications (DLG-KDD2022).” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4906–7, 2022. https://doi.org/10.1145/3534678.3542907.
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    • Wu, L., P. Cui, J. Pei, L. Zhao, and X. Guo. “Graph Neural Networks: Foundation, Frontiers and Applications.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4840–41, 2022. https://doi.org/10.1145/3534678.3542609.
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    • Zhang, Y., S. Gao, J. Pei, and H. Huang. “Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 2515–23, 2022. https://doi.org/10.1145/3534678.3539415.
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    • Zhang, Y., H. Gao, J. Pei, and H. Huang. “Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction.” In Www 2022  Proceedings of the Acm Web Conference 2022, 1352–61, 2022. https://doi.org/10.1145/3485447.3512182.
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    • Zhang, Y., L. Wu, Q. Shen, Y. Pang, Z. Wei, F. Xu, B. Long, and J. Pei. “Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation.” In Www 2022  Proceedings of the Acm Web Conference 2022, 2153–62, 2022. https://doi.org/10.1145/3485447.3512088.
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    • Pang, Y., L. Wu, Q. Shen, Y. Zhang, Z. Wei, F. Xu, E. Chang, B. Long, and J. Pei. “Heterogeneous global graph neural networks for personalized session-based recommendation.” In Wsdm 2022  Proceedings of the 15th Acm International Conference on Web Search and Data Mining, 775–83, 2022. https://doi.org/10.1145/3488560.3498505.
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    • Chen, Nuo, Linjun Shou, Ming Gong, and Jian Pei. “From good to best: Two-stage training for cross-lingual machine reading comprehension.” In Proceedings of the Aaai Conference on Artificial Intelligence, 36:10501–8, 2022.
    • Liang, S., L. Shou, J. Pei, M. Gong, W. Zuo, X. Zuo, and D. Jiang. “Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding.” In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Emnlp 2022, 9903–18, 2022.
    • Lin, W., L. Shou, M. Gong, P. Jian, Z. Wang, B. Byrne, and D. Jiang. “Combining Unstructured Content and Knowledge Graphs into Recommendation Datasets.” In Ceur Workshop Proceedings, 3294:45–52, 2022.
    • Luo, X., J. Pei, Z. Cong, and C. Xu. “On Shapley Value in Data Assemblage Under Independent Utility.” In Proceedings of the Vldb Endowment, 15:2761–73, 2022. https://doi.org/10.14778/3551793.3551829.
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    • Ren, H., L. Shou, J. Pei, N. Wu, M. Gong, and D. Jiang. “Lexicon-Enhanced Self-Supervised Training for Multilingual Dense Retrieval.” In Findings of the Association for Computational Linguistics: Emnlp 2022, 444–59, 2022.
    • Singh, G., L. Chu, L. Wang, J. Pei, Q. Tian, and Y. Zhang. “Mining Minority-Class Examples with Uncertainty Estimates.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13141 LNCS:258–71, 2022. https://doi.org/10.1007/978-3-030-98358-1_21.
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    • Zhang, Y., R. Bao, J. Pei, and H. Huang. “Toward Unified Data and Algorithm Fairness via Adversarial Data Augmentation and Adaptive Model Fine-tuning.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2022-November:1317–22, 2022. https://doi.org/10.1109/ICDM54844.2022.00174.
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    • Banitalebi-Dehkordi, A., N. Vedula, J. Pei, F. Xia, L. Wang, and Y. Zhang. “Auto-Split: A General Framework of Collaborative Edge-Cloud AI.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 2543–53, 2021. https://doi.org/10.1145/3447548.3467078.
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    • Liang, S., M. Gong, J. Pei, L. Shou, W. Zuo, X. Zuo, and D. Jiang. “Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 3231–39, 2021. https://doi.org/10.1145/3447548.3467196.
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    • Pei, J., F. Zhu, Z. Cong, X. Luo, H. Liu, and X. Mu. “Data Pricing and Data Asset Governance in the AI Era.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4058–59, 2021. https://doi.org/10.1145/3447548.3470818.
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    • Wu, L., J. Tang, Y. Xia, J. Pei, and X. Guo. “The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21).” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4167–68, 2021. https://doi.org/10.1145/3447548.3469470.
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    • Zhang, Q., B. Gu, C. Deng, S. Gu, L. Bo, J. Pei, and H. Huang. “AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 3917–27, 2021. https://doi.org/10.1145/3447548.3467169.
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    • Zhou, Z., L. Chu, C. Liu, L. Wang, J. Pei, and Y. Zhang. “Towards Fair Federated Learning.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4100–4101, 2021. https://doi.org/10.1145/3447548.3470814.
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    • Zhu, F., and J. Pei. “The Third International Workshop on Smart Data for Blockchain and Distributed Ledger (SDBD2021): Joint Workshop with SIGKDD 2021 Trust Day.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 4185–86, 2021. https://doi.org/10.1145/3447548.3469441.
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    • Hua, M., J. Pei, A. W. C. Fu, X. Lin, and H. F. Leung. “Efficiently answering top-k typicality queries on large databases.” In 33rd International Conference on Very Large Data Bases, Vldb 2007  Conference Proceedings, 890–901, 2007.
    • Liu, Y., L. Chen, J. Pei, Q. Chen, and Y. Zhao. “Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays.” In Proceedings  Fifth Annual Ieee International Conference on Pervasive Computing and Communications, Percom 2007, 37–46, 2007. https://doi.org/10.1109/PERCOM.2007.23.
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    • Pei, J., B. Jiang, X. Lin, and Y. Yuan. “Probabilistic skylines on uncertain data.” In 33rd International Conference on Very Large Data Bases, Vldb 2007  Conference Proceedings, 15–26, 2007.
    • Varde, Aparna, and Jian Pei. “PIKM 2007 foreword.” In International Conference on Information and Knowledge Management, Proceedings, iii–iii, 2007.
    • Wong, R. C. W., A. W. C. Fu, K. Wang, and J. Pei. “Minimality attack in privacy preserving data publishing.” In 33rd International Conference on Very Large Data Bases, Vldb 2007  Conference Proceedings, 543–54, 2007.
    • Wong, R. C. W., Y. Liu, J. Yin, Z. Huang, A. W. C. Fu, and J. Pei. “(α, k)-anonymity based privacy preservation by lossy join.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4505 LNCS:733–44, 2007. https://doi.org/10.1007/978-3-540-72524-4_75.
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    • Wong, Raymond Chi-Wing, Yubao Liu, Jian Yin, Zhilan Huang, Ada Wai-Chee Fu, and Jian Pei. “(&ALPHA-anonymity based privacy preservation by lossy join.” In Advances in Data and Web Management, Proceedings, 4505:733-+, 2007.
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    • Xiong, Z., W. Wang, and J. Pei. “Active rules termination analysis through conditional formula containing updatable variable.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4505 LNCS:281–92, 2007. https://doi.org/10.1007/978-3-540-72524-4_31.
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    • Zhou, B., and J. Pei. “Sketching landscapes of page farms.” In Proceedings of the 7th Siam International Conference on Data Mining, 593–98, 2007. https://doi.org/10.1137/1.9781611972771.67.
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    • On, B. W., E. Elmacioglu, D. Lee, J. Kang, and J. Pei. “An effective approach to entity resolution problem using Quasi-Clique and its application to digital libraries.” In Proceedings of the Acm/Ieee Joint Conference on Digital Libraries, 2006:51–52, 2006. https://doi.org/10.1145/1141753.1141761.
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    • Pei, J., Y. Yuan, X. Lin, W. Jin, M. Ester, Q. Liu, W. Wang, Y. Tao, J. X. Yu, and Q. Zhang. “Towards multidimensional subspace skyline analysis.” In Acm Transactions on Database Systems, 31:1335–81, 2006. https://doi.org/10.1145/1189769.1189774.
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    • Xie, T., and J. Pei. “MAPO: Mining API usages from open source repositories.” In Proceedings  International Conference on Software Engineering, 54–57, 2006. https://doi.org/10.1145/1137983.1137997.
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    • Xu, Y., K. Wang, A. W. C. Fu, R. She, and J. Pei. “Classification spanning correlated data streams.” In International Conference on Information and Knowledge Management, Proceedings, 132–41, 2006. https://doi.org/10.1145/1183614.1183637.
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    • Li, J., H. Li, L. Wong, J. Pei, and G. Dong. “Minimum description length principle: Generators are preferable to closed patterns.” In Proceedings of the National Conference on Artificial Intelligence, 1:409–14, 2006.
    • Pekerskaya, I., J. Pei, and K. Wang. “Mining changing regions from access-constrained snapshots: A cluster-embedded decision tree approach.” In Journal of Intelligent Information Systems, 27:215–42, 2006. https://doi.org/10.1007/s10844-006-9951-9.
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    • Aggarwal, C. C., J. Pei, and B. Zhang. “On privacy preservation against adversarial data mining.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 2006:510–16, 2006. https://doi.org/10.1145/1150402.1150460.
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    • Jiuyong, L., R. C. W. Wong, A. W. C. Fu, and P. Jian. “Achieving k-anonymity by clustering in attribute hierarchical structures.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4081 LNCS:405–16, 2006.
    • On, B. W., E. Elmacioglu, D. Lee, J. Kangt, and J. Pei. “Improving grouped-entity resolution using Quasi-Cliques.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 1008–15, 2006. https://doi.org/10.1109/ICDM.2006.85.
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    • Tao, Y., K. Xiao, and J. Pei. “SUBSKY: Efficient computation of skylines in subspaces.” In Proceedings  International Conference on Data Engineering, 2006:66–75, 2006. https://doi.org/10.1109/ICDE.2006.149.
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    • Tao, Yufei, Xiaokui Xiao, and Jian Pei. “Subsky: Efficient computation of skylines in subspaces.” In 22nd International Conference on Data Engineering (Icde’06), 65–65, 2006.
    • Wang, H., J. Yin, J. Pei, P. S. Yu, and J. X. Yu. “Suppressing model overfitting in mining concept-drifting data streams.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 2006:736–41, 2006. https://doi.org/10.1145/1150402.1150496.
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    • Xu, J., W. Wang, J. Pei, X. Wang, B. Shi, and A. W. C. Fu. “Utility-based anonymization using local recoding.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 2006:785–90, 2006. https://doi.org/10.1145/1150402.1150504.
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    • Zhang, J., X. Zhou, W. Wang, B. Shi, and J. Pei. “Using High Dimensional Indexes to Support Relevance Feedback Based Interactive Images Retrieval∗.” In Vldb 2006  Proceedings of the 32nd International Conference on Very Large Data Bases, 1211–14, 2006.
    • Zhu, W., J. Pei, J. Yin, and Y. Xie. “Granularity adaptive density estimation and on demand clustering of concept-drifting data streams.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4081 LNCS:322–31, 2006. https://doi.org/10.1007/11823728_31.
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    • Pei, J., D. Jiang, and A. Zhang. “Mining cross-graph quasi-cliques in gene expression and protein interaction data.” In Proceedings  International Conference on Data Engineering, 353–54, 2005. https://doi.org/10.1109/ICDE.2005.87.
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    • Wang, H., J. Pei, and P. S. Yu. “Online mining of data streams: Applications, techniques and progress.” In Proceedings  International Conference on Data Engineering, 1146, 2005. https://doi.org/10.1109/ICDE.2005.101.
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    • Liu, C., K. Wu, and J. Pei. “A dynamic clustering and scheduling approach to energy saving in data collection from wireless sensor networks.” In 2005 Second Annual Ieee Communications Society Conference on Sensor and Adhoc Communications and Networks, Secon 2005, 2005:374–85, 2005. https://doi.org/10.1109/SAHCN.2005.1557091.
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    • Pei, J., D. Jiang, and A. Zhang. “On mining cross-graph quasi-cliques.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 228–38, 2005. https://doi.org/10.1145/1081870.1081898.
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    • Pei, J., J. Liu, H. Wang, K. Wang, P. S. Yu, and J. Wang. “Efficiently mining frequent closed partial orders (extended abstract).” In Proceedings  Ieee International Conference on Data Mining, Icdm, 753–56, 2005. https://doi.org/10.1109/ICDM.2005.57.
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    • Pei, J., W. Jin, M. Ester, and Y. Tao. “Catching the best views of skyline: A semantic approach based on decisive subspaces.” In Vldb 2005  Proceedings of 31st International Conference on Very Large Data Bases, 1:253–64, 2005.
    • Wang, W., C. Wang, Y. Zhu, B. Shi, J. Pei, X. Yan, and J. Han. “GraphMiner: A structural pattern-mining system for large disk-based graph databases and its applications.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 879–81, 2005.
    • Ye, J., X. Zhou, J. Pei, L. Chen, and L. Zhang. “A stratification-based approach to accurate and fast image annotation.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3739 LNCS:284–96, 2005. https://doi.org/10.1007/11563952_26.
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    • Yu, H., J. Pei, S. Tang, and D. Yang. “Mining the most general multidimensional summarization of "probable groups" in data warehouses.” In Proceedings of the International Conference on Scientific and Statistical Database Management, Ssdbm, 185–94, 2005.
    • Cho, M., J. Pei, and D. W. Cheung. “Cross table cubing: Mining iceberg cubes from data warehouses.” In Proceedings of the 2005 Siam International Conference on Data Mining, Sdm 2005, 461–65, 2005. https://doi.org/10.1137/1.9781611972757.41.
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    • Dong, G., C. Jiang, J. Pei, J. Li, and L. Wong. “Mining succinct systems of minimal generators of formal concepts.” In Lecture Notes in Computer Science, 3453:175–87, 2005. https://doi.org/10.1007/11408079_17.
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    • Jiang, D., J. Pei, and A. Zhang. “A general approach to mining quality pattern-based clusters from microarray data.” In Lecture Notes in Computer Science, 3453:188–200, 2005. https://doi.org/10.1007/11408079_18.
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    • Pei, Jian, Jian Liu, Haixun Wang, Ke Wang, Philip S. Yu, and Jianyong Wang. “Efficiently mining frequent closed partial orders.” In Fifth Ieee International Conference on Data Mining (Icdm’05), 4-pp, 2005.
    • Ramakrishnan, Raghu, Rakesh Agrawal, Johann-Christoph Freytag, Toni Bollinger, Christopher W. Clifton, Saso Dzeroski, Jochen Hipp, et al. “Data mining: The next generation.” In Dagstuhl Seminar Proceedings, 2005.
    • Wang, H., J. Pei, and P. S. Yu. “Pattern-based similarity search for microarray data.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 814–19, 2005. https://doi.org/10.1145/1081870.1081978.
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    • Wang, H., and J. Pei. “A random method for quantifying changing distributions in data streams.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3721 LNAI:684–91, 2005. https://doi.org/10.1007/11564126_73.
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    • Wang, Haixun, Jian Pei, and Philip S. Yu. “Online mining data streams: Problems, applications and progress.” In Proc. the 21st International Conference on Data Engineering, Icde�05, 5–8, 2005.
    • Wang, H., F. Chu, W. Fan, S. Y. Philip, and J. Pei. “A fast algorithm for subspace clustering by pattern similarity.” In Proceedings of the International Conference on Scientific and Statistical Database Management, Ssdbm, 16:51–60, 2004.
    • Deng, L., J. Pei, J. Ma, and D. L. Lee. “A rank sum test method for informative gene discovery.” In Kdd 2004  Proceedings of the Tenth Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 410–19, 2004. https://doi.org/10.1145/1014052.1014099.
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    • Jiang, D., J. Pei, M. Ramanathan, C. Tang, and A. Zhang. “Mining coherent gene clusters from gene-sample-time microarray data.” In Kdd 2004  Proceedings of the Tenth Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 430–39, 2004. https://doi.org/10.1145/1014052.1014101.
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    • Jiang, Daxin, Jian Pei, Murali Ramanathan, Chun Tang, and Aidong Zhang. “Mining coherent gene clusters from three-dimensional microarray data.” In Proceedings of the 10th Acm Sigkdd International Conference on Knowledge Discovery and Data Mining (Kdd�04), 22–25, 2004.
    • Jiang, Daxin, Jian Pei, and Aidong Zhang. “GPX: interactive mining of gene expression data.” In Proceedings of the Thirtieth International Conference on Very Large Data Bases Volume 30, 1249–52, 2004.
    • Pei, Jian, Shambhu J. Upadhyaya, Faisal Farooq, and Venugopal Govindaraju. “Data mining for intrusion detection: techniques, applications and systems.” In Proceedings. 20th International Conference on Data Engineering, 877–877, 2004.
    • Wang, C., M. Hong, J. Pei, H. Zhou, W. Wang, and B. Shi. “Efficient pattern-growth methods for frequent tree pattern mining.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3056:441–51, 2004. https://doi.org/10.1007/978-3-540-24775-3_54.
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    • Wang, C., W. Wang, J. Pei, Y. Zhu, and B. Shi. “Scalable mining of large disk-based graph databases.” In Kdd 2004  Proceedings of the Tenth Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 316–25, 2004. https://doi.org/10.1145/1014052.1014088.
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    • Jiang, D., J. Pei, and A. Zhang. “Interactive exploration of coherent patterns in time-series gene expression data.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 565–70, 2003. https://doi.org/10.1145/956750.956820.
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    • Lakshmanan, L. V. S., J. Pei, and Y. Zhao. “QC-Trees: An Efficient Summary Structure for Semantic OLAP.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 64–75, 2003.
    • Lakshmanan, L. V. S., J. Pei, and Y. Zhao. “SOCQET: Semantic OLAP with Compressed Cube and Summarization.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 658, 2003.
    • Pei, J., X. Zhang, M. Cho, H. Wang, and P. S. Yu. “MaPle: A fast algorithm for maximal pattern-based clustering.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 259–66, 2003.
    • Tang, C., A. Zhang, and J. Pei. “Mining phenotypes and informative genes from gene expression data.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 655–60, 2003. https://doi.org/10.1145/956750.956835.
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    • Wang, J., J. Han, and J. Pei. “CLOSET+: Searching for the best strategies for mining frequent closed itemsets.” In Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 236–45, 2003. https://doi.org/10.1145/956750.956779.
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    • Dong, Guozhu, Jiawei Han, Laks V. S. Lakshmanan, Jian Pei, Haixun Wang, and Philip S. Yu. “Online mining of changes from data streams: Research problems and preliminary results.” In Proceedings of the 2003 Acm Sigmod Workshop on Management and Processing of Data Streams, 739–47, 2003.
    • Huang, Y., H. Xiong, S. Shekhar, and J. Pei. “Mining confident co-location rules without a support threshold.” In Proceedings of the Acm Symposium on Applied Computing, 497–501, 2003. https://doi.org/10.1145/952613.952630.
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    • Jiang, D., J. Pei, and A. Zhang. “DHC: A density-based hierarchical clustering method for time series gene expression data.” In Proceedings  3rd Ieee Symposium on Bioinformatics and Bioengineering, Bibe 2003, 393–400, 2003. https://doi.org/10.1109/BIBE.2003.1188978.
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    • Kum, Hye-Chung, Jian Pei, Wei Wang, and Dean Duncan. “ApproxMAP: Approximate mining of consensus sequential patterns.” In Proceedings of the 2003 Siam International Conference on Data Mining, 311–15, 2003.
    • Lakshmanan, L. V. S., J. Pei, and Y. Zhao. “Efficacious data cube exploration by semantic summarization and compression.” In Proceedings  29th International Conference on Very Large Data Bases, Vldb 2003, 1125–28, 2003. https://doi.org/10.1016/b978-012722442-8/50121-x.
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    • Pei, J., G. Dong, W. Zou, and J. Han. “On computing condensed frequent pattern bases.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 378–85, 2002.
    • Han, J., J. Wang, G. Dong, J. Pei, and K. Wang. “CubeExplorer: Online exploration of data cubes.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 626, 2002.
    • Wang, T., S. Tang, D. Yang, J. Gao, Y. Wu, and J. Pei. “COMMIX: Towards effective web information extraction, integration and query answering.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 620, 2002.
    • Wang, T., S. Tang, D. Yang, J. Gao, Y. Wu, and J. Pei. “COMMIX: Towards Effective Web Information Extraction, Integration and Query Answering.” In Proceedings of the 2002 Acm Sigmod International Conference on Management of Data, Sigmod 2002, 620, 2002. https://doi.org/10.1145/564691.564774.
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    • Chen, Yixin, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, and Jianyong Wang. “Online analytical processing stream data: Is it feasible?” In Dmkd, 2002.
    • Chen, Yixin, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W. Wah, and Jianyong Wang. “Olaping stream data: Is it feasible.” In Proc. Workshop on Research Issues in Data Mining and Knowledge Discovery, Acm Sigmod, 53–58, 2002.
    • Lakshmanan, Laks V. S., Jian Pei, and Jiawei Han. “Quotient cube: How to summarize the semantics of a data cube.” In Vldb’02: Proceedings of the 28th International Conference on Very Large Databases, 778–89, 2002.
    • Pei, J., J. Han, and W. Wang. “Mining sequential patterns with constraints in large databases.” In International Conference on Information and Knowledge Management, Proceedings, 18–25, 2002. https://doi.org/10.1145/584792.584799.
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    • Pei, Jian, Jia-wei Han, and Wei Wang. “Constraint-based sequential pattern mining in large databases.” In Proc. 2002 Int�L Conf. Information and Knowledge Management (Cikm�02), 18–25, 2002.
    • Li, W., J. Han, and J. Pei. “CMAR: Accurate and efficient classification based on multiple class-association rules.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 369–76, 2001.
    • Pei, J., J. Han, H. Lu, S. Nishio, S. Tang, and D. Yang. “H-mine: Hyper-structure mining of frequent patterns in large databases.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 441–48, 2001.
    • Han, J., H. Jamil, Y. Lu, L. Chen, Y. Liao, and J. Pei. “DNA-Miner: A system prototype for mining DNA sequences.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 618, 2001.
    • Dong, G., J. Han, J. Lam, J. Pei, and K. Wang. “Mining multi-dimensional constrained gradients in data cubes.” In Vldb 2001  Proceedings of 27th International Conference on Very Large Data Bases, 321–30, 2001.
    • Han, J., J. Pei, G. Dong, and K. Wang. “Efficient computation of iceberg cubes with complex measures.” In Proceedings of the Acm Sigmod International Conference on Management of Data, 1–12, 2001. https://doi.org/10.1145/375663.375664.
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    • Han, Jiawei, Laks V. S. Lakshmanan, and Jian Pei. “Scalable frequent-pattern mining methods: an overview.” In Tutorial Notes of the Seventh Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 5–1, 2001.
    • Han, Jiawei, and Jian Pei. “Pattern growth methods for sequential pattern mining: Principles and extensions.” In Workshop on Temporal Data Mining, 7th Acm Sigkdd International Conference on Knowledge Discovery and Data Mining (Kdd�01). Acm Press, 2001.
    • Pei, J., J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M. C. Hsu. “PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth.” In Proceedings  International Conference on Data Engineering, 215–24, 2001.
    • Pinto, H., J. Han, J. Pei, K. Wang, Q. Chen, and U. Dayal. “Multi-dimensional sequential pattern mining.” In International Conference on Information and Knowledge Management, Proceedings, 81–88, 2001. https://doi.org/10.1145/502598.502600.
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    • Han, J., J. Pei, B. Mortazavi-Asl, Q. Chen, U. Dayal, and M. C. Hsu. “FreeSpan: Frequent pattern-projected sequential pattern mining.” In Proceeding of the Sixth Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 355–59, 2000.
    • Han, J., J. Pei, and Y. Yin. “Mining Frequent Patterns without Candidate Generation.” In Sigmod 2000  Proceedings of the 2000 Acm Sigmod International Conference on Management of Data, 1–12, 2000. https://doi.org/10.1145/342009.335372.
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    • Pei, J., J. Han, B. Mortazavi-Asl, and H. Zhu. “Mining access patterns efficiently from web logs.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1805:396–407, 2000. https://doi.org/10.1007/3-540-45571-x_47.
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    • Pei, J., J. Han, and B. Mortazavi-Asl. “Zhu. H. 2000. Mining access patterns efficiently from Web Logs.” In Proceedings Of, 2000.
    • Pei, J., and J. Han. “Can we push more constraints into frequent pattern mining?” In Proceeding of the Sixth Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 350–54, 2000. https://doi.org/10.1145/347090.347166.
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    • Pei, Jian, Jiawei Han, Runying Mao, and Runying others. “CLOSET: An efficient algorithm for mining frequent closed itemsets.” In Acm Sigmod Workshop on Research Issues in Data Mining and Knowledge Discovery, 4:21–30, 2000.
    • Chu, Haixun Wang Fang, Wei Fan, S Yu Philip, and Jian Pei. “A Fast Algorithm for Subspace Clustering by Pattern Similarity.” In Proceedings of the 16th International Conference on Scientific and Statistical Database Management (Ssdbm�04), 1099:20–00, n.d.
    • Pei, J., J. Han, B. Mortazavi-asl, H. Pinto, Q. Chen, and U. Dayal. “chun Hsu, M.(2001). Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth.” In Icde�01: Proceedings of the 2001 International Conference on Data Engineering, 215–215, n.d.
    • Pei, Jian, Jiawei Han, Behzad Mortazavi-asl, and Hua Zhu. “Mining Access Patterns E ciently from Web Logs?” In Proc. of Pakdd’Oo, n.d.
    • Pei, Jian, Jiawei Han, and Runying Mao. “CLOSET: An E cient Algorithm for Mining Frequent Closed Itemsets.” In Acm Sigmod Workshop on Research Issues in Data Mining and Knowledge Discovery, 21–30, n.d.

  • Theses and Dissertations

    • Pei, Jian. “PATTERN-GROWTH METHODS FOR FREQUENT,” 2002.

  • Preprints

    • Zhou, Ce, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, et al. “A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT,” February 18, 2023.
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    • Hu, Xia, Lingyang Chu, Jian Pei, Weiqing Liu, and Jiang Bian. “Model Complexity of Deep Learning: A Survey,” March 8, 2021.
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    • Cong, Zicun, Lingyang Chu, Yu Yang, and Jian Pei. “Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test,” November 1, 2020.
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    • Liu, Junhao, Linjun Shou, Jian Pei, Ming Gong, Min Yang, and Daxin Jiang. “Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation,” October 27, 2020.
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    • Zhang, Xingyao, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen, and Daxin Jiang. “A Graph Representation of Semi-structured Data for Web Question Answering,” October 14, 2020.
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    • Jiang, Honglu, Jian Pei, Dongxiao Yu, Jiguo Yu, Bei Gong, and Xiuzhen Cheng. “Applications of Differential Privacy in Social Network Analysis: A Survey,” October 6, 2020.
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    • Pei, Jian. “A Survey on Data Pricing: from Economics to Data Science,” September 9, 2020.
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    • Shou, Linjun, Shining Bo, Feixiang Cheng, Ming Gong, Jian Pei, and Daxin Jiang. “Mining Implicit Relevance Feedback from User Behavior for Web Question Answering,” June 13, 2020.
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• Teaching & Mentoring
• 

  Recent Courses

  • CBB 526: Data Science 2023
  • CBB 590: Special Topics in Computational Biology 2023
  • COMPSCI 394: Research Independent Study 2023
  • COMPSCI 526: Data Science 2023
  • COMPSCI 590: Advanced Topics in Computer Science 2023
  • ECE 583: Data Science 2023
  • ECE 590: Advanced Topics in Electrical and Computer Engineering 2023
  • COMPSCI 393: Research Independent Study 2022
  • ECE 590: Advanced Topics in Electrical and Computer Engineering 2022
  • ECE 899: Special Readings in Electrical Engineering 2022

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