Books

  • B. C. M. Fung, K. Wang, A. W.-C. Fu, and P. S. Yu. Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques (Table of Content), Data Mining and Knowledge Discovery Series. 376 pages, Chapman & Hall/CRC, August 2010. ISBN: 9781420091489

    Survey papers

  • B. Fung, K. Wang, R. Chen, P. Yu. Privacy-Preserving Data Publishing: A Survey of Recent Developments. ACM Computing Surveys, Vol. 42, Issue No 4, 1-53, June 2010, ACM Press

    Publication

  • Anandharaju Durai Raju, Ke Wang. Low Carbon Footprint Training for CNNs with Temporal Max-Pooling. CIKM 2024.

  • Amirhossein Ansar, Ke Wang, and Pulei Xiong. Out-of-Distribution Aware Classification for Tabular Data. CIKM 2024.

  • Ehsan Hoseinzade, Ke Wang. Graph Neural Network Approach to Semantic Type Detection in Tables. PAKDD 2024.

  • Ziqi Xu, Jixue Liu, Debo Cheng, Jiuyong Li, Lin Liu, and Ke Wang. Disentangled Representation with Causal Constraints for Counterfactual Fairness. PAKDD 2023.

  • Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan, and Ke Wang. TEM: High Utility Metric Differential Privacy on Text. SDM 2023.

  • Ziqi Xu, Debo Cheng, Jiuyong Li, Jixue Liu, Lin Liu, and Ke Wang. Disentangled Representation for Causal Mediation Analysis. AAAI 2023.

  • Lovedeep Gondara and Ke Wang. PubSub-ML: A Model Streaming Alternative to Federated Learning. Privacy Enhancing Technologies Symposium (PETS) 2023.

  • YONGJIE WANG, KE WANG, CHENG LONG, and CHUNYAN MIAO. Summarizing User-Item Matrix By Group Utility Maximization. Accepted by ACM TKDD, Dec 2022

  • Haochen Zhang, Zhiyun Peng, Junjie Tang, Ming Dong, Ke Wang, Wenyuan Li. A multi-layer extreme learning machine refined by sparrow search algorithm and weighted mean filter for short-term multi-step wind speed forecasting. Sustainable Energy Technologies and Assessments, Volume 50, March 2022, 101698

  • Anandharaju Durai Raju and Ke Wang. LockBoost: Detecting Malware Binaries by Locking False Alarms. IJCNN 2022

  • Zhenlong Xu, Ziqi Xu, Jixue Liu, Debo Cheng, Jiuyong Li, Lin Liu, and Ke Wang. Assessing Classifier Fairness with Collider Bias. PAKDD 2022.

  • Ricardo S. Carvalho, Ke Wang, Lovedeep Gondara. Incorporating Item Frequency for Differentially Private Set Union. AAAI 2022.

  • Lovedeep Gondara, Ke Wang, Ricardo S. Carvalho. Differentially Private Ensemble Classifiers for Data Streams. WSDM 2022.

  • Yonghui Xu, Shengjie Sun, Huiguo Zhang, Chang An Yi, Yuan Miao, Dong Yang, Xiaonan Meng, Yi Hu, Ke Wang, Huaqing Min, HengJie Song, and Chuanyan Miao. Time-aware Graph Embedding: A temporal smoothness and task-oriented approach. ACM Transactions on Knowledge Discovery from Data, Volume 16, Issue 3, June 2022, Article No.: 56, pp 1-23, https://doi.org/10.1145/3480243

  • Yongjie Wang, Ke Wang, Cheng Long, and Chunyan Miao. Summarizing User-Item Matrix By Group Utility Maximization. ICDM 2021.

  • Yongjie Wang, Qinxu Ding, Ke Wang, Yue Liu, Xingyu Wu, Jinglong Wang, Yong Liu, Chunyan Miao. The Skyline of Counterfactual Explanations for Machine Learning Decision Models. CIKM 2021

  • Lovedeep Gondara, Ricardo Silva Carvalho, and Ke Wang. Training Differentially Private Neural Networks With Lottery Tickets. The European Symposium on Research in Computer Security (ESORICS) 2021

  • Yuncheng Wu, Ke Wang, Ruoyang Guo, Zhilin Zhang, Dan Zhao, Hong Chen, and Cuiping Li. Enhanced Privacy Preserving Group Nearest Neighbor Search. TKDE, Vol. 33, No. 2, 459-473, Feb 2021.

  • Jiaxi Tang, Hongyi Wen, Ke Wang. Revisiting Adversarially Learned Injection Attacks Against Recommender Systems. RecSys 2020.

  • Lovedeep Gondara and Ke Wang. Differentially Private Survival Function Estimation. Machine Learning for Healthcare 2020.

  • Lovedeep Gondara and Ke Wang. Differentially Private Small Dataset Release Using Random Projections. UAI 2020

  • Ricardo Silva Carvalho, Ke Wang, Lovedeep Gondara, and Chun Yan Miao. Differentially Private Top-k Selection via Stability on Unknown Domain. UAI 2020

  • Yue Wang, Ke Wang, Chun Yan Miao. Truth Discovery against Strategic Sybil Attack in Crowdsourcing. SIGKDD 2020

  • Weipeng Lin, Ke Wang, Zhilin Zhang, Ada Waichee Fu, Raymond Chi-Wing Wong, Cheng Long, and Chun Yan Miao. Towards Secure and Efficient Equality Conjunction Search over Outsourced Databases. IEEE Transactions on Cloud Computing, 2020.

  • Zhiyun Peng, Sui Peng, Lidan Fu, Binchun Lu, Junjie Tang, Ke Wang, Wenyuan Li. Novel Deep Learning Based Ensemble Model with Data Denoising Function for Short-Term Wind Speed Forecasting. Energy Conversion and Management, 2020.

  • Zhilin Zhang, Ke Wang, Weipeng Lin, Ada Wai-Chee Fu, Raymond Chi-Wing Wong. Repeatable Oblivious Shuffling of Large Outsourced Data Blocks. ACM Symposium on Cloud Computing 2019 (SoCC'19).

  • Zhilin Zhang, Ke Wang, Weipeng Lin, Ada Wai-Chee Fu, Raymond Chi-Wing Wong. Practical Access Pattern Privacy by Combining PIR and Oblivious Shuffle. CIKM 2019.

  • Weipeng Lin, Ke Wang, Zhilin Zhang, Ada Waichee Fu, Raymond Chi-Wing Wong, Long Cheng. Class Indistinguishability for Outsourcing Equality Conjunction Search. CLOUD 2019. (253-270)

  • Amin Milani Fard, Ebrahim Bagheri, Ke Wang. Relationship Prediction in Dynamic Heterogeneous Information Networks. ECIR 2019, Winner of the Best System Paper. (19-34)

  • Ryan McBride, Ke Wang, Zhouyang Ren, Wenyuan Li. Cost-Sensitive Learning to Rank. AAAI 2019 (4570-4577)

  • Zhilin Zhang, Ke Wang, Chen Lin and Weipeng Lin. Secure Top-k Inner Product Retrieval. CIKM 2018 (77-86)

  • Jiaxi Tang, Ke Wang. Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System. KDD 2018 (2289-2298)

  • Hongwei Liang, Ke Wang. Top-k Route Search through Submodularity Modeling of Recurrent POI Features. SIGIR 2018 (545-554). [datasets and code on GitHub]

  • Ying Liu, Hui Peng, Yuncheng Wu, Juru Zeng, Hong Chen, Ke Wang, Weiling Lai and Cuiping Li. Secure data aggregation with integrity verification in Wireless Sensor Networks. DASFAA 2018 (717-733)

  • Lovedeep Grondara, Ke Wang. MIDA: Multiple Imputation using Denoising Autoencoders. PAKDD 2018 (260-272)

  • Yuncheng Wu, Ke Wang, Zhilin Zhang, Weipeng Lin, Hong Chen, Cuiping Li. Privacy Preserving Group Nearest Neighbor Search. EDBT 2018 (277-288)

  • Jiaxi Tang and Ke Wang. Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding. WSDM 2018 (565-573)

  • Lovedeep Gondara and Ke Wang. Recovering Loss to Followup Information Using Denoising Autoencoders. IEEE Big Data 2017, Special Session on Intelligent Data Mining (12 pages)

  • Xiangling Zhang, Yueguo Chen, Jun Chen, Xiaoyong Du, Ke Wang and Ji-Rong Wen. Entity Set Expansion via Knowledge Graphs. SIGIR 2017 (1101-1104)

  • Yi Dai, Zhouyang Ren, Ke Wang, Wenyuan Li, Zhenwen Li, Wei Yan. Optimal Sizing and Arrangement of Tidal Current Farm. IEEE Transactions on Sustainable Energy, Vol 9, issue 1, 27 June 2017 (168-177)

  • Weipeng Lin, Ke Wang, Zhilin Zhang, Hong Chen. Revisiting Security Risks of Asymmetric Scalar Product Preserving Encryption and Its Variants. IEEE International Conference on Distributed Computing Systems (ICDCS 2017) (1116-1125)

  • Zhouyang Ren, Ke Wang, Wenyuan Li, Liming Jin, Yi Dai. Probabilistic Power Flow Analysis of Power Systems Incorporating Tidal Current Generation. IEEE Transactions on Sustainable Energy, Vol 8, Issue 3, Feb 2017 (1195-1203)

  • Ryan McBride, Ke Wang, Viswanadh Nekkanti, Wenyuan Li. Risk Clearance with Guaranteed Precision. SDM 2017 (9 pages)

  • Chenyi Zhang, Hongwei Liang, Ke Wang. Trip Recommendation Meets Real World Constraints: POI Availability, Diversity and Traveling Time Uncertainty . ACM Transactions on Information Systems (TOIS), Volume 35 Issue 1, September 2016, Article No. 5 (28 pages)

  • Wei Xie, Feida Zhu, Jing Jiang, Ee-Peng Lim, and Ke Wang. TopicSketch: Real-time Bursty Topic Detection from Twitter . TKDE, Volume: 28, Issue: 8, Aug. 1 2016 (2216 - 2229)

  • Ke Wang, Peng Wang, Ada Fu, Raymond Wong. Generalized Bucketization Scheme for Flexible Privacy Settings . Information Sciences, 2016, Volume 348, 20 June 2016 (377-393)

  • Hongwei Liang, Ke Wang, Feida Zhu. Mining Social Ties Beyond Homophily. ICDE 2016 (421-432)

  • Junqiang Liu, Ke Wang, Benjamin Fung. Mining High Utility Patterns in One Phase without Generating Candidates . TKDE, Volume: 28, Issue: 5, May 1 2016 (1245 - 1257)

  • Chenyi Zhang and Ke Wang. POI Recommendation through Cross-Region Collaborative Filtering. KAIS, Volume 46 Issue 2, February 2016 (369-387)

  • Yue Wang, Ke Wang, Ada Wai-Chee Fu, and Raymond Chi-Wing Wong. KeyLabel Algorithm for Keyword Search in Large Graphs. IEEE Big Data 2015 (857-864)

  • Wei Xie, Feida Zhu, Siyuan Liu, and Ke Wang. Modelling Cascades Over Time in Microblogs. IEEE Big Data 2015 (677-686)

  • Aungon Nag Radon, Ke Wang, Uwe Glaesser, Hans Wehn, and Andrew Westwell-Roper. Contextual Verification for False Alarm Reduction in Maritime Anomaly Detection. IEEE Big Data 2015 (1123-1133)

  • Xiaoning Xu; Chuancong Gao; Jian Pei; Ke Wang; Abdullah Al-Barakati. Continuous Similarity Search for Evolving Queries. KAIS, September 2016, Volume 48, Issue 3 (649-678)

  • Chenyi Zhang, Hongwei Liang, Ke Wang, Jianling Sun. Personalized Trip Recommendation with POI Availability and Uncertain Traveling Time. CIKM 2015 (911-920). The runner-up for the best student paper award.

  • Shuaiqiang Wang, Yun Wu, Byron J. Gao, Ke Wang, Hady W. Lauw, and Jun Ma. A Cooperative Coevolution Framework for Parallel Learning to Rank. TKDE, Vol 27, Issue 12 - Dec. 2015, Vol.27 (3152-3165)

  • Lei Dong, Xuan Chen, Jianxiang Zhu, Hong Chen, Ke Wang, Cuiping Li. A Secure Collusion-aware and Probability-aware Range Query Processing in Tiered Sensor Networks. The 34th IEEE Symposium on Reliable Distributed Systems, 2015. (10 pages)

  • Chao Han and Ke Wang. Sensitive Disclosures under Differential Privacy Guarantees. IEEE BigData Congress 2015. (8 pages)

  • Ke Wang, Chao Han, Ada Waichee Fu, Raymond Chi Wing, Philip S. Yu. Reconstruction Privacy: Enabling Statistical Learning. EDBT 2015. (12 pages)

  • Loc Do, Hady W. Lauw, Ke Wang. Mining Revenue-Maximizing Bundling Configuration. PVLDB 2015. (12 pages)

  • Chenyi Zhang, Ke Wang, Ee-peng Lim, Qinneng Xu, Jianling Sun, and Hongkun Yu. Are Features Equally Representative? A Feature-Centric Recommendation. AAAI 2015. (6 pages)

  • Chenyi Zhang, Jianling Sun, Ke Wang. Latent Tunnel Based Information Propagation in Microblog Networks. In Social Network Analysis - Community Detection and Evolution, Series: Lecture Notes in Social Networks, Edited by Missaoui, Rokia and Sarr, Idrissa. 2014, XVIII, 272 pp.

  • Ryan McBride, Ke Wang, Wenyuan Li. Classification by CUT: Clearance Under Threshold. IEEE ICDM 2014 conference, December 2014. (10 pages)

  • Ada Fu, Ke Wang, Raymond C Wong, Jia Wang, Minhao Jiang. Small Sum Privacy and Large Sum Utility in Data Publishing. Journal of Biomedical Informatics, 2014 (20-31)

  • Xiaoying Zhang, Hong Chen, Ke Wang, Hui Peng, Yongjian Fan, Deying Li. Rotation-based Privacy-preserving Data Aggregation in Wireless Sensor Networks. IEEE International Conference on Communications 2014 (6 pages)

  • Ismael A Vergara, Maja Tarailo-Graovac, Christian Frech, Jun Wang, Ting Zhang, Zhaozhao Qin, Rong She, Jeffrey SC Chu, Ke Wang and Nansheng Chen. Genome-wide variations in a natural isolate of the nematode Caenorhabditis elegans. BMC Genomics, 2014 (1471-2164)

  • Chenyi Zhang, Xueyi Zhao, Ke Wang, Jianling Sun. Content + Attributes: a Latent Factor Model for Recommending Scientific Papers in Heterogeneous Academic Networks. ECIR 2014 (12 pages)

  • Chenyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, En-Peng Lim. Latent Factor Transition for Dynamic Collaborative Filtering SDM 2014 (9 pages) (also available at here )

  • Wenyuan Li, Ke Wang and Wijarn Wangdee. Load Data Cleansing and Bus Load Coincidence Factors. In Smart Grids: Clouds, Communications, Open Source, and Automation, Edited by David Bakken , and Krzysztof Iniewski, CRC Press 2014, Print ISBN: 978-1-4822-0611-1, eBook ISBN: 978-1-4822-0612-8.

  • Wei Xie, Feida Zhu, Jing Jiang, Ee-Peng Lim, and Ke Wang. TopicSketch: Real-time Bursty Topic Detection from Twitter. ICDM, Dallas, Texas, December 7-10, 2013 (10 pages).

  • Peng Zhao, Xue Li and Ke Wang. Feature Extraction from Microblogs for Comparison of Products and Services. The 14th International Conference on Web Information System Engineering, 2013. (10 pages)

  • Yin Chu Yeh, Wenyuan Li, Adriel Lau, and Ke Wang. Identifying PCB Contaminated Transformers through Active Learning. IEEE Transactions on Power Systems, Vol. 28, No. 4, Nov. 2013 (3999-4006)

  • Chenyi Zhang, Jianling Sun, Ke Wang. Information Propagation in Microblog Networks. IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM 2013) (7 pages)

  • Amin Milani Fard and Ke Wang. Neighborhood Randomization for Link Privacy in Social Network Analysis. World Wide Web Journal, Special Issue on "Trusting Social Web", July 2013 (9-32)

  • Zhihui Guo, Wenyuan Li, Adriel Lau, Tito Inga-Rojas, Ke Wang. Trend Based Periodicity Detection for Load Curve Data. IEEE Power & Energy Society General Meeting, 2013 (5 pages)

  • Cheng Long, Raymond Chi-Wing Wong, Ke Wang and Ada Wai-Chee Fu. Collective Spatial Keyword Queries: A Distance Owner-Driven Approach. SIGMOD 2013 (12 pages)

  • R. Chen, B. C. M. Fung, N. Mohammed, B. C. Desai, and K. Wang. Privacy-preserving trajectory data publishing by local suppression. Information Sciences (INS), 231: 83-97 (2013): Special Issue on Data Mining for Information Security, Elsevier. [ ISI impact factor: 3.291, 5-year: 3.089 ]

  • Junqiang Liu and Ke Wang. Anonymizing Bag-valued Sparse Data by Semantic Similarity Based Clustering. KAIS,35(2): 435-461 (2013), 2013.

  • Yubao Liu, Raymond Chi-Wing Wong, Ke Wang, Zhijie Li, Cheng Chen, and Zhitong Chen. A New Approach for Maximizing Bichromatic Reverse Nearest Neighbor Search. KAIS, 36(1): 23-58 (2013), 2013.

  • Junqiang Liu, Ke Wang, and Benjamin Fung. Direct Discovery of High Utility Itemsets without Candidate Generation. ICDM 2012 (6 pages)

  • A. M. Fard, K. Wang, P. Yu. Limiting Link Disclosure in Social Network Analysis through Subgraph-Wise Perturbation. EDBT 2012 (11 pages)

  • Hady Lauw, Ee Peng Lim, Ke Wang. Quality and Leniency in Online Collaborative Rating Systems. ACM Transactions on the Web (TWEB), Vol. 6, No. 1, March 2012 (27 pages)

  • Nigel Medforth, Ke Wang. Privacy Risk In Graph Stream Publishing For Social Network Applications. ICDM 2011 (10 pages)

  • Zhihui Guo, Wenyuan Li, Adriel Lau, Tito Inga-Rojas, and Ke Wang. Detecting X-Outliers in Load Curve Data in Power Systems. IEEE Transactions on Power Systems, Vol. 27, No. 2, May 2012, 875-884.

  • Rong She, Jeffrey Shih-Chieh Chu, Bora Uyar, Jun Wang, Ke Wang and Nansheng Chen. genBlastG: extending BLAST to be a high performance gene finder. Bioinformatics (2011), Vol. 27, No. 15, 2141-2143, 2011

  • Shuaiqiang Wang, Byron Gao, Ke Wang, Hady W. Lauw. Parallel Learning to Rank for Information Retrieval. ACM SIGIR (poster) 2011 (2 pages)

  • Shuaiqiang Wang, Byron Gao, Ke Wang, Hady Lauw. CCRank: Parallel Learning to Rank with Cooperative Coevolution. AAAI Conference on Artificial Intelligence (AAAI) 2011 (6 pages)

  • R. Wong, A. Fu, K. Wang, J. Pei, P. Yu. Can the utility of anonymized data be used for privacy breaches? ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 5, No. 3, August 2011 (26 pages)

  • Zhengzheng Xing, Jian Pei, Philip S. Y, and Ke Wang. Interpretable Features for Early Classification on Time Series. SDM 2011 (12 pages)

  • Christopher C. Yang, Daniel Zeng, Ke Wang, Antonio Sanfilippo, Herbert H. Tsang, Min-Yuh Day, Uwe Glässer, Patricia L. Brantingham, Hsinchun Chen: IEEE International Conference on Intelligence and Security Informatics, ISI 2010, Vancouver, BC, Canada, May 23-26, 2010, Proceedings IEEE 2010.

  • Ke Wang, Yabo Xu, Ada Fu, and Raymond Wong. Anonymizing Temporal Data. ICDM 2010 (6 pages)

  • Raymond Wong, Ada Fu, Ke Wang, Yabo Xu, Jian Pei, and Philip Yu. Probabilistic Inference Protection on Uncertain Data. ICDM 2010 (6 pages)

  • Jungqiang Liu and Ke Wang. Enforcing Vocabulary k-Anonymity by Semantic Similarity Based Clustering. ICDM 2010.

  • J. Chen, A. Lau, W. Li and K. Wang. Load Analyzer: a Software Tool for Load Data Analysis. CIGRE Canada 2010 Conference: Power System Solutions for a Cleaner, Greener World. Vancouver, 2010

  • Chaytor, R., Wang, K. Small Domain Randomization: Same Privacy, More Utility. The 36th International Conference on Very Large Data Bases (VLDB 2010).

  • Amin Milani Fard, Ke Wang.An Efficient Clustering Approach to Web Query Ananymization. SECRYPT 2010.

  • Junqiang Liu, Ke Wang. Anonymizing Transaction Data by Integrating Suppression and Generalizatioa. PAKDD 2010

  • Jiyi Chen, Wenyuan Li, Adriel Lau, Jiguo Cao and Ke Wang. Automated Load Curve Data Cleansing in Power Systems. IEEE Transactions on Smart Grid, September 2010, Vol. 1, No. 2, pp 213-221.

  • Y. Xu, K. Wang, R. C. W. Wong, A. Fu. Publishing Skewed Sensitive Microdata. SDM 2010

  • R. She, J. Chu, K. Wang, and N. Chen. Fast and Accurate Gene Prediction by Decision Tree Classification. SDM 2010

  • R. C. W. Wong, A. Fu, J. Liu, K. Wang, Y. Xu. Global Privacy Guarantee in Serial Data Publishing. ICDE 2010

  • J. Q. Liu and K. Wang. On Optimal Anonymization for l+-Diversity. ICDE 2010

  • Rhonda Chaytor, Ke Wang, Patricia Brantingham. Fine-Grain Perturbation for Privacy Preserving Data Publishing. ICDM 2009

  • Hady W. Lauw, Ee-Peng Lim, and Ke Wang. On Mining Rating Dependencies in Online Collaborative Rating Networks. PAKDD 2009

  • Yabo Xu, Ke Wang, Guoliang Yang, Ada Fu. Online Anonymity for Personalized Web Services. CIKM 2009

  • H. W. Lauw, L. E. Peng, K. Wang. On Mining Rating Dependencies in Online Collaborative Rating Networks. PAKDD 2009

  • B. C. M. Fung, K. Wang, L. Wang, and P. C. K. Hung. Privacy-Preserving Data Publishing for Cluster Analysis. Data & Knowledge Engineering (DKE). Vol. 68, Issue 6, June 2009, 552-575, Elsevier Science Publishers B. V

  • N. Mohammed, B. C. M. Fung, K. Wang, and P. C. K. Hung. Privacy-preserving data mashup. In Proceedings of the 12th International Conference on Extending Database Technology (EDBT 2009), Saint-Petersburg, Russia: ACM Press, March 2009.

  • K. Wang, Y. Xu, A. Fu, R. Wong. FF-Anonymity: When Quasi-Identifiers Are Missing. ICDE 2009

  • Y. Xu, B. Fung, K. Wang, A. Fu, and J. Pei. Publishing Sensitive Transactions for Itemset Utility . ICDM 2008

  • R. C. W. Wong, J. Li, A. W. C. Fu. and K. Wang. (alpha, k)-anonymous data publishing. Journal of Intelligent Information Sys tems, Volume 33, Number 2 / October, 2009

  • Xinghuo Zeng; Jian Pei; Ke Wang; Jinyan Li. PADS: A Simple Yet Effective Pattern-Aware Dynamic Search Method for Fast Maximal Frequent Pattern . Knowledge and Information Systems, Volume 20, Issue 3 (2009), Page 375

  • Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, and Jian Pei. Anonymization based Attack in Privacy Preserving Data Publishing . ACM Transactions on Databases Systems (TODS), Volume 34, Issue 2, Jun., 2009

  • R. She, J. Chu, K. Wang, J. Pei, J. Chen. genBlastA: enabling BLAST to identify homologous gene sequences. Genome Research, January 2009 19:143-149; doi:10.1101/gr.082081.108 (2007 impact factor: 11.224)

  • R. Wong, J. Pei, A. Fu, K. Wang. Online Skyline Analysis with Dynamic Preferences on Nominal Attributes . TKDE, pp1-15, Vol. 21, No. 1, Jan., 2009

  • Y. Xu, K. Wang, A. Fu and P. Yu. Anonymizing Transaction Databases for Publication . SIGKDD 2008

  • B. Fung, K. Wang, L. Wang, M. Debbabi. A framework for privacy-preserving cluster analysis . IEEE International Conference on Intelligence and Security Informatics, 2008.

  • Proceedings of the Eighth SIAM International Conference on Data Mining, 2008. Edited by Mohammed J. Zaki, Ke Wang, Chid Apte, and Haesun Park

  • H. W. Lauw, E. P. Lim, K. Wang. Bias and Controversy in Evaluation Systems. TKDE, Vol. 20, No. 11, pp. 1490-1504, Apr., 2008

  • B. Fung, K. Wang, A. Fu, J. Pei. Anonymity for Continuous Data Publishing . EDBT 2008.

  • X. Zeng, J. Pei, I. Vergaraz M. Nesbittz, K. Wang, N. Chen. OrthoCluster: A New Tool for Mining Syntenic Blocks and Applications in Comparative Genomics . EDBT 2008

  • R. She, K. Wang, A. Fu, Y. Xu. Computing Join Aggregates over Private Tables. Invited paper to DaWak 2007 Special Issue, International Journal of Data Warehousing and Mining (IJDWM), Vol. 4, Issue 4, Sept-Dec 2008

  • Y. Xu, K. Wang, A. Fu, R. She, and J. Pei. Privacy-preserving data stream classfication (Book Chapter), in Privacy-Preserving Data Models and Algorithms (Springer), Ed. C. Aggarwal, P. Yu, 2007.

  • R. Wong, A. Fu, K. Wang, and J. Pei. Minimality Attack in Privacy Preserving Data Publishing. VLDB 2007

  • R. Wong, J. Pei, A. Fu, and K. Wang. Mining Favorable Facets. SIGKDD 2007

  • R. She, K. Wang, A. Fu, Y. Xu. Computing Join Aggregates over Private Tables . DaWak 2007 [One of five best papers]

  • Jian Pei, Jian Xu, Zhibin Wang, Wei Wang, Ke Wang. Maintaining K-Anonymity against Incremental Updates . SSDBM 2007

  • Y. Xu, B. Zhang, Z. Chen, K. Wang. Privacy-Enhancing Personalized Web Search. WWW 2007

  • H. W. Lauw, E. P. Lim, K. Wang. Summarizing Review Scores of Unequal Reviewers. SIAM International Conference on Data Mining 2007

  • B. Fung, K. Wang, P. S. Yu. Anonymizing Classification Data for Privacy Preservation. IEEE Transaction on Knowledge and Data Engineering 19(5) 711-725, 2007

  • K. Wang, B. C. M. Fung, and P. S. Yu. Handicapping Attacker's Confidence: An Alternative to k-Anonymization. Invited paper, Knowledge and Information Systems: An International Journal, 11(3):345-368, April 2007.

  • T. Jiang, A. H. Tan, K. Wang. Mining Generalized Associations of Semantic Relations from Textual Web Content. IEEE Transactions on Knowledge and Data Engineering Knowledge and Data Engineering, Special Issue on Semantic Web, Vol. 19 No. 2 2007.

  • Y. T. Lai, K. Wang, D. Ling, H. Shi and J. Zhang. Direct Marketing When There Are Voluntary Buyers. ICDM 2006. "slides

  • Y. Xu, K. Wang, A. Fu, R. She and J. Pei. Classification Spanning Correlated Data Streams, CIKM 2006

  • K. Wang and B. Fung. Anonymizing Sequential Releases. SIGKDD 2006. Slides

  • H. W. Lauw, E. P. Lim, and K. Wang. Bias and Controversy: Beyond the Statistical Deviation. SIGKDD 2006

  • R. C. W. Wong, J. Li, A. W. C. Fu. and K. Wang. (alpha, k)-Anonymity: An Enhanced k-Anonymity Model for Privacy-Preserving Data Publishing. SIGKDD 2006

  • J. Pei, H. Wang, J. Liu, K. Wang, J. Wang, and P. S. YU. Discovering Frequent Closed Partial Orders from Strings. IEEE Transaction on Knowledge and Data Engineering, VOL. 18, NO. 11, NOVEMBER 2006

  • K. Wang, Y. Xu, R. She, P. Yu. Classification Spanning Private Databases. AAAI 2006

  • I. Pekerskaya, J. Pei, K. Wang. Miming changing regions from access-constrained snapshots: a cluster-embedded decision tree approach. Journal of Intelligent Information Systems, Special Issue on Mining Spatio-Temporal Data, Volume 27, Number 3, 215-242, November, 2006.

  • K. Wang, Y. Jiang, and A. Tuzhilin. Mining Actionable Patterns by Role Models. ICDE 2006.

  • Y. Jiang, K. Wang, A. Tuzhilin, and A. Fu. Mining Patterns That Respond to Actions. ICDM 2005.

  • K. Wang, B. Fung, and P. Yu. Template-Based Privacy Preservation in Classification Problems. ICDM 2005.

  • A. Fu, R. Wong, and K. Wang. Privacy-Preserving Frequent Pattern Mining across Private Databases. ICDM 2005.

  • J. Pei, J. Liu, H. Wang, K. Wang, P. Yu and J. Wang. Efficiently Mining Frequent Closed Partial Orders (Extended Abstract) ICDM 2005.

  • S. Zhou and K. Wang. Localization Site Prediction for Membrane Proteins by Integrating Rule and SVM Classification. IEEE Transaction on Knowledge and Data Engineering, Vol. 17, No. 10, December 2005

  • M. Choy, J. Pei and K. Wang. Answering Ad Hoc Aggregate Queries from Data Streams Using Prefix Aggregate Trees, KAIS: Knowledge and Information Systems - An International Journal, 2005.

  • R.C.W. Wong, A. Fu and K. Wang. Data mining for inventory item selection with cross-selling considerations. Journal of Data Mining and Knowledge Discovery, Volume 11, 2005, 81-112

  • K. Wang, S. Zhou, Q. Yang and J.M.S. Yeung. Mining customer value: from association rules to direct marketing. Journal of Data Mining and Knowledge Discovery, Vol. 11, No. 1, July 2005, 57-80

  • K. Wang, B. Fung and G. Dong. Integrating private databases for data analysis. IEEE International Conference on Intelligence and Security Informatics 2005 (IEEE ISI-2005), 171-182 Springer-Verlag

  • K. Wang, Y. Xu, P. S. Yu, and R. She. Building decision trees on records linked through key references. SIAM International Conference on Data Mining (SDM) 2005

  • R. She, K. Wang, Y. Xu and P.S. Yu. Pushing feature selection ahead of join. SIAM International Conference on Data Mining (SDM) 2005

  • B. Fung, K. Wang and P. Yu. Top-Down Specialization for Information and Privacy Preservation. ICDE 2005, 205-216, Software, Slides

  • K. Wang, J. Yuelong, J. Yu, G. Dong and J. Han. Divide-and-Approximate: a novel constraint push strategy for iceberg cube mining. IEEE Transaction on Knowledge and Data Engineering, Vol. 17, No. 3, March 2005, 354-368

  • B. Fung, K. Wang and M. Ester. Hierarchical document clustering. The Encyclopedia of Data Warehousing and Mining, Idea Group Reference, 2004.

  • S. Zhou and K. Wang. Profit mining. The Encyclopedia of Data Warehousing and Mining, Idea Group Reference, 2004.

  • K. Wang, Y. Xu, J. Yu. Scalable sequential pattern mining for biological sequences. Thirteenth Conference on Information and Knowledge Management 2004 (CIKM 2004), Nov, 2004.

  • K. Wang, P. Yu, and S. Chakraborty. Bottom-up generalization: a data mining solution to privacy protection. ICDM 2004

  • G. Dong, J. Han, J. Lam, J. Pei, K. Wang, W. Zou. Mining constrained gradients in large databases. IEEE Transaction on Knowledge and Data Engineering, Vol 16, No. 8, August 2004 (also available here

  • Q. Yang, T. Li, K. Wang. Building association rule based sequential classifiers for web document prediction. Journal of Data Mining and Knowledge Discovery, 8(3), 253-273, 2004. Also available here

  • R. She, F. Chen, K. Wang, M. Ester, J. L. Gardy, F. S. L. Brinkman. Identifying bacterial outer membrane proteins using frequent subsequences - a data mining approach, ISMB03 (Intelligent Systems for Molecular Biology, 2003), Brisbane, July, 2003

  • R. C. W. Wong, A. W. C. Fu, K. Wang. MPIS: Maximal-profit item selection with cross-selling considerations. ICDM, Melbourne, Nov, 2003

  • R. She, F. Chen, K. Wang, M. Ester, J. L. Gardy, F. S. L. Brinkman. Frequent-subsequence-based prediction of outer membrane proteins". SIGKDD 2003, Washington D.C., August, 2003, Slides

  • K. Wang, Y. Jiang, L. V.S. Lakshmanan. Mining unexpected rules by pushing user dynamics". SIGKDD 2003, Washington D.C., August, 2003, Slides

  • Jennifer Gardy, Cory Spencer, Ke Wang, Martin Ester, Tusnady GE, Simon, Sujun Hua, Katalin deFays, Christophe Lamb ert, Kenta Nakai, Fiona Brinkman. PSORT-B: Improving protein subcellular localization prediction for Gram-negative bacteria. Special web software issue, Nucleic Acids Research, Vol. 31, No. 13, 1-5, July 2003 ( a web-based version of the PSORT-B software for prediction of protein subcellular localization for Gram-negative bacteria )

  • K. Wang, S. Zhou, A. Fu, J. Yu. Mining changes of classification by correspondence tracing. SIAM International Conference on Data Mining 2003, May 2003, San Francisco Slides

  • B. C.M. Fung, K. Wang, M. Ester. Hierarchical document clustering using frequent itemsets SIAM International Conference on Data Mining 2003, San Francisco Slides , Software

  • Q. Yang, T. Li and K. Wang. Web-log cleaning for constructing Sequential classifiers International Journal of Applied Artificial Intelligence, Vol. 17, No. 5, Special Issue on Data Cleaning and Data Preparation in Data Mining. May/June 2003.

  • K. Wang, Y. He, J. Han Pushing support constraints into association rules mining, IEEE Transaction on Knowledge and Data Engineering, Vol. 15, No. 3, May/June 2003, 642-658

  • K. Wang, Y. Jiang, J. X. Yu, G. Dong, J. Han. Pushing aggregate constraints by divide-and-approximate, ICDE 2003, Bangalore, India, Slides

  • K. Wang, S. Zhou, J. M. S. Yeung, Q. Yang. Mining customer value: from association rules to direct marketing, ICDE 2003, Bangalore, India

  • Eric Ka Ka Ng, Ada Wai-chee Fu, Ke Wang, "Mining association rules from stars" The 2002 IEEE International Conference on Data Mining, Maebashi TERRSA, Maebashi City, Japan, December 9 - 12, 2002

  • Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han "Mining frequent item sets by opportunistic projection" SIGKDD 2002, Edmonton, Slides

  • Ke Wang and Ming-Yen Su "Item selection by "hub-authority" profit ranking" SIGKDD 2002, Edmonton, Slides

  • Jiawei Han, Jianyong Wang, Guozhu Dong, Jian Pei, Ke Wang "CubeExplorer: online exploration of data cubes" SIGMOD 2002 system demo paper

  • Ke Wang, Liu Tang, Jiawei Han, Junqiang Liu "Top down FP-Growth for association rule mining" , the 6th Pacific Area Conference on Knowledge Discovery and Data Mining (PAKDD-2002), May 6-8, Taipei, Taiwan. Slides

  • Gao Cong, Lan Yi, Bing Liu and Ke Wang "Discovering frequent substructures from hierarchical semi-structured data", the Second SIAM International Conference on Data Mining (SDM-2002), April 11-13, 2002, Hyatt Regency, Crystal City, Arlington, VA, USA

  • Ke Wang, Senqiang Zhou, Jiawei Han "Profit mining: from patterns to actions", 2002 International Conference on Extending Database Technology (EDBT 2002). Slides

  • Ke Wang, Yu He, David Cheung, Francis Chin "Mining confident rulees without support requirement" , the 10th ACM International Conference on Information and Knowledge Management (CIKM 2001), Atlanta. Slides

  • Helen Pinto, Jiawei Han, Jian Pei, Ke Wang, Qiming Chen, Umeshwar Dayal "Multi-dimensional sequential pattern mining" , the 10th ACM Intednational Conference on Information and Knowledge Management (CIKM 2001), Atlanta. Slides

  • Guozhu Dong, Jiawei Han, Joyce Lam, Jian Pei, Ke Wang "Mining multi-dimensional constrained gradients in data cubes" , VLDB 2001

  • Ian Tianyi Li, Qiang Yang, Ke Wang "Classification pruning for web-request prediction" , 10th International Conference on WWW, 2001

  • Sonny H.S. Chee, Jiawei Han, Ke Wang "RecTree: An efficient collaborative filtering method" , Data Warehousing and Knowledge Discovery (DaWaK), Munich, Germany, Sept. 2001

  • Jiawei Han, Jian Pei, Guozhu Dong, Ke Wang "Efficient computation of iceberg cubes with complex measures", ACM SIGMOD 2001.

  • K. Wang, H.Q. Liu, "Mining Is-Part-of association patterns from semistructured data", the 9th IFIP 2.6 Working Conference on Database Semantics (DS-9), April 2001, Hong Kong

  • K. Wang, S. Zhou, Y. He, " Hierarchical classification of real life documents", the First SIAM International Conference on Data Mining, April 2001, Chicago. Slides

  • K. Wang, Y. He, "User-defined association Mining", PAKDD 2001, April, 2001, Hong Kong. Slides

  • K. Wang, Y. He, J. Han, "Mining frequent itemsets using support constraints", VLDB 2000, Cairo, Sept 2000, 43-52. Slides

  • K. Wang, S. Zhou, Y. He, "Growing decision trees on support-less association rules", SIGKDD 2000, Boston, August 2000, 265-269, Software

  • K. Wang, H.Q. Liu, "Discovering association of structure from semistructured objects". IEEE Transactions on Knowledge and Data Engineering, Vol 12, No. 3, May/June 2000, 353-371

  • W. Zhang and K. Wang, "An efficient evaluation of a fuzzy equi-join using fuzzy equality indicators". The IEEE Transactions on Knowledge and Data Engineering, Vol. 12, No. 2, March/April, 2000, 225-237

  • K. Wang, C. Xu, B. Ling, "Clustering transactions using large items", ACM CIKM'99 (Eighth International Conference on Information and Knowledge Management) November 2-6, 1999, Kansas City, 483-490, Software

  • K. Wang, S. Zhou, S.C. Liew, "Building hierarchical classifiers using class proximity", VLDB 1999, September 1999, Edinburgh, UK, Morgan Kaufmann, 363-374

  • B. Liu, W. Hsu, K. Wang, S. Chen, "Visually aided exploration of interesting association rules". Third Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), April 1999, Beijing. Lectures Notes in Artificial Intelligence 1574, 380-389

  • K. Wang, B. C. Ooi, S. Y. Sung, "P-Tree: A B-Tree index for lists". The International Conference on Database Systems for Advanced Applications, April 1999, Taiwan, IEEE Computer Society, 221-228

  • K. Wang, B. Liu, I. Png, "How many shoppers buy beer and diapers together?". Sunday Times Review, Oct 11, 1998, Singapore, pp 35

  • K. Wang and B. Liu, "Concurrent discretization of multiple attributes". The Pacific Rim International Conference on Artificial Intelligence (PRICAI 98), August 1998, Singapore, 250-259

  • B. Liu, K. Wang, L. F. Mun and X. Z. Qi, "Using decision tree induction for discovering holes in data". Pacific Rim International Conference on Artificial Intelligence (PRICAI 98), August 1998, Singapore, 182-193

  • K. Wang, W. Tay, B. Liu, "Interestingness-based interval merger for numeric association rules" . The International Conference on Knowledge Discovery and Data Mining, August 1998, New York City, AAAI, 121-128 (plenary presentation)

  • K. Wang, H.Q. Liu, "Discovering typical structures of documents: a road map approach" . The ACM SIGIR Conference on Research and Development in Information Retrieval, August 1998, 146-154

  • K. Wang, S. Sundaresh, "Selecting features by vertical compactness of data" . Feature Extraction: Construction and Selection. Edited by H. Liu and H. Motoda, 1998, Kluwer Academic Publishers, 71-83

  • K. Wang, H.Q. Liu, "Mining nested association patterns" . The SIGMOD97 Workshop on Research Issues on Data Mining and Knowledge Discovery, May 1997

  • K. Wang, "Discovering patterns from large and dynamic sequential data" , Special Issues on data Mining and Knowledge Discovery, Journal of Intelligent Information Systems, 9(1), 8-33, 1997, Kluwer Academic Publishers

  • K. Wang, H.C. Goh, "Minimum splits based discretization for continuous features" . The International Joint Conference on Artificial Intelligence, August 1997, Nagoya, Japan, 942-947

  • K. Wang, H.Q. Liu, "Schema discovery from semistructured data" . The International Conference on Knowledge Discovery and Data Mining, August 1997, Newport Beach, AAAI, 271-274

  • K. Wang, S. Sundaresh, "Selecting features by vertical compactness of data" . The International Conference on Knowledge Discovery and Data Mining, August 1997, Newport Beach, AAAI, 275-278

  • W. Zhang, K. Wang, "Fuzzy equi-join and its evaluation". The International Conference on Intelligent Systems, June 1997, Boston

  • K. Wang, W. Zhang, S.C. Chau, "Weakly indenpendent database schemes" . Acta Informatica 34, 1-22 (1997), Springer-Verlag, Federal Republic of Germany

  • W.C. Tan, K. Wang, L.S. Wong, "A graphical user interface to genome multidatabases" . Journal of Database Management, 9(1), 24-32, 1997, Idea Group Publishing, USA

  • K. Wang, J. Tan, "Incremental discovery of sequential patterns" . The ACM-SIGMOD's 96 Data Mining Workshop: On Research Issues on Data Mining and Knowledge Discovery, Montreal, Canada, May 1996, 95-102

  • S.Y. Sung, K. Wang, B.L. Chua, "Data mining in a large database environment". The 1996 IEEE International Conference on Systems, Man and Cybernetics, 1996, 988-993

  • W.C. Tan, K. Wang, L.S. Wong, "QUICK - a graphical user interface to multiple databases" . The Seventh International Workshop on Database and Expert Systems Applications, Sept 1996, Zurich, Switzerland, IEEE Computer Society Press, 404-409

  • K. Wang, W. Zhang,"Detecting data inconsistency for multidatabases" . The Ninth International Conference on Parallel and Distributed Computing Systems (PDCS'96), Vol II, Dejon, France, Sept 1996, 657-663

  • W. Zhang, K. Wang, and S.C. Chau, "Data partition and parallel evaluation of datalog programs". IEEE Transactions on Knowledge and Data Engineering, 7(1), Feb. 1995, IEEE Press, New York, 163-176

  • K. Wang, W. Zhang, S.C. Chau, "Decomposition of magic rewriting" . Journal of Association for Computing Machinery, 42(2), March 1995, ACM Press, New York, 329-381

  • K. Wang, "Some positive results for boundedness of multiple recursive rules" . Lecture Notes in Computer Science 893, Springer-Verlag, the International Conference on Database Theory, January 1995, Czech Republic, 383-396

  • K. Wang, W. Zhang, S.C. Chau, "Indexed step-wise semi-naive evaluation for recursive queries" . Special Issue of Journal of Computing and Information, 1995, Peterborough, Canada, 485-511

  • K. Wang and L. Y. Yuan, "First-order logic characterization of program properties". IEEE Transactions on Knowledge and Data Engineering, 6(4), August 1994, IEEE Press, New York, 518-533

  • K. Wang, W. Zhang, S.C. Chau, "Minimize linear mutual recursion by rule unfolding". The Fifth International Conference on Computing and Information, May 1993, Ontario, Canada, IEEE Computer Society Press, Los Alamitos, 98-102

  • H.J. Hernandez and K. Wang, "On the boundedness of constant-time-maintainable database schemes". SIAM Journal on Computing, 22(1), Feb. 1993, 29-45, SIAM, Philadelphia

  • K. Wang and M.H. Graham, "Constant-time-maintainability: a generalization of independence". ACM Transactions on Database Systems, 17(2), June 1992, 201-246, ACM Press, New York

  • K. Wang, "On characterizing boundedness of database schemes with bounded dependencies". Theoretical Computer Science 100, 1992, 347-364, Elsevier Science Publishers B.V., North-Holland, The Netherlands

  • K. Wang, "Polynomial tests of normal forms and some related results". Journal of Computer Science and Technology, 7(1), Jan. 1992, 75-82, Science Press, China, and Allerton Press, Inc. USA

  • K. Wang and L. Y. Yuan, "Preservation of integrity constraints in definite datalog programs". Information Processing Letter, 44(4), December 1992, 185-193, Elsevier Science Publishers B.V., North-Holland, The Netherlands

  • K. Wang and L.Y. Yuan, "Enforce constraints in archival database". The Fourth International Conference on Computing and Information, 1992, Toronto, Canada, IEEE Computer Society Press, Los Alamitos, 397-400

  • K. Wang and L.Y. Yuan, "Enforce database constraints by historical information". The Fourth International Conference on Computing and Information, 1992, Toronto, Canada, 369-372

  • W. Zhang, K. Wang, and S.C. Chau, "Data partition: a practical parallel evaluation of datalog programs". The First International Conference on Parallel and Distributed Information Systems, ACM SIGMOD & SIGARCH/IEEE Computer Society, Dec 1991, Miami Beach, IEEE Computer Society Press, Los Alamitos, 98-105

  • K. Wang and L.Y. Yuan, "First-order logic reducible programs". The Seventh International Conference on Data Engineering, 1991, Kobe (Japan), IEEE Computer Society Press, Los Alamitos, 746-755

  • K. Wang and L.Y. Yuan, "Incremental database design revisited". Lecture Notes in Computer Science 497, Springer Verlag. The Third International Conference on Computing and Information, 1991, Ottawa, Canada, 219-230

  • K. Wang, "Polynomial time designs towards both BCNF and efficient data manipulation". The ACM SIGMOD International Conference on Management of Data, 1990, Atlantic City, ACM Press, New York, 74-83

  • M.H. Graham and K. Wang, "On the equivalence of an egd to a set of Fd's". The Journal of Association for Computing Machinery, 37(3), July 1990, 474-490, ACM Press, New York

  • K. Wang, "Can constant-time-maintainability be more practical?" The Eighth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1989, Philadelphia, ACM Press, New York, 120-127

  • M.H. Graham and K. Wang, "Constant time maintenance or the triumph of fd's". The Fifth ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, 1986, Boston, ACM Press, New York, 202-216