Ke Wang
Database, Data Mining

Professor, Computing Science
MSc, Georgia Institute of Technology
PhD, Georgia Institute of Technology

School of Computing Science
Simon Fraser University
8888 University Drive
Burnaby, British Columbia, Canada V5A 1S6
Tel: 7787824667
Fax: 7787823045

Database and Data Mining Laboratory

Software for Download:

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

  • Temporal Probabilistic Matrix Factorization : A temporal recommender based on matrix factorization. Publication: Chenyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, En-Peng Lim. Latent Factor Transition for Dynamic Collaborative Filtering . SDM 2014

  • CUT Classification : A clearance threshold based approach to cost sensitive classification. Publication: Ryan McBride, Ke Wang, Wenyuan Li. Classification by CUT: Clearance Under Threshold . IEEE ICDM 2014

  • Top-Down Specialization (TDS 1.0): Generalize a table to satisfy the k-anonymity privacy requirement and preserve information for classification. Publication: B.C.M. Fung, K. Wang, and P.S. Yu. "Top-Down Specialization for Information and Privacy Preservation". ICDE 2005

  • Frequent Itemset-based Hierarchical Clustering (FIHC 1.0): Construct a document cluster hierarchy from a set of unlabeled documents based on frequent itemsets. Publication: B.C.M. Fung, K. Wang, and M. Ester. "Hierarchical Document Clustering Using Frequent Itemsets". SDM 2003

    Recent Publication:

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

  • 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

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

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

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

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

  • 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)

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

  • Hongwei Liang, Ke Wang, Feida Zhu. Mining Social Ties Beyond Homophily. ICDE 2016

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









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