Publications

(This is a selective list. The full list of publications can be found from here)

  1. Yifan Hao, Huiping Cao, and Erick Draayer: CNN Approaches to Classify Multivariate Time Series Using Class-specific Features. In Proc. of 2020 IEEE International Conference on Smart Data Services (SMDS), pages 1-8.
  2. Yifan Hao and Huiping Cao: A New Attention Mechanism to Classify Multivariate Time Series. In Proc. of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI) Main track. 2020: Pages 1999-2005. (Acceptance rate: 12.6%).
    https://doi.org/10.24963/ijcai.2020/277.
    The source code for this paper can be downloaded from this github repository.
  3. Qixu Gong, Jiefei Liu and Huiping Cao: CSQ System: A System to Support Constrained Skyline Queries on Transportation Networks (Demo paper). CSQ System: A System to Support Constrained Skyline Queries on Transportation Networks (Demo paper).
    In Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2020: 1746-1749.
    [https://doi.org/10.1109/ICDE48307.2020.00160][Presentation slide] [Presentation video][Demo video]
    The source code for this paper can be downloaded from this github repository.
  4. Yifan Hao, Huiping Cao, Abdullah Mueen, and Sukumar Brahma: Identify Significant Phenomenon-specific Variables for Multivariate Time Series. In IEEE Transactions on Knowledge and Data Engineering (TKDE). 2019. [https://ieeexplore.ieee.org/document/8798763]
    The source code for this paper can be downloaded from this github repository.
  5. Edgar Ceh-Varela and Huiping Cao: Recommending Packages of Multi-criteria Items to Groups. In Proc. of IEEE Intl. Conf. on Web Services (ICWS) 2019: 273-282. (Acceptance rate: 18%) [https://doi.org/10.1109/ICWS.2019.00054]
    The source code for this paper can be downloaded from this github repository.
  6. Qixu Gong, Huiping Cao, Parth Nagarkar: Skyline Queries Constrained by Multi-Cost Transportation Networks. In Proc. of IEEE Intl. Conf. on Data Engineering (ICDE), 2019: 926-937. [https://doi.org/10.1109/ICDE.2019.00087]
    The source code for this paper can be downloaded from this github repository.
  7. Ian Goetting, Elisabeth Baseman, Huiping Cao: Causal Relationships amongst Sensors in the Trinity Supercomputer: work in progress. In Proceedings of the First Workshop on Machine Learning for Computing Systems. Co-located with The 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC’18).
    [PDF] [PDF file in ACM library]
  8. Chuan Hu, Huiping Cao, Qixu Gong: Sub-Gibbs Sampling: a New Strategy for Inferring LDA. In Proc. of Intl. Conf. on Data Mining (ICDM 2017), 907-912. (Overall acceptance rate: 19.9%).
    [PDF] [http://doi.ieeecomputersociety.org/10.1109/ICDM.2017.113. ]
    The source code for this paper can be downloaded from this github repository.
  9. Chuan Hu, Huiping Cao: Aspect-Level Influence Discovery from Graphs.
    IEEE Trans. Knowl. Data Eng. 28(7): 1635-1649 (2016).
    [PDF] [http://dx.doi.org/10.1109/TKDE.2016.2538223]
    The source code for this paper can be downloaded from this github repository.
  10. James Obert, Inna Pivkina, Hong Huang, Huiping Cao: Proactively applied encryption in multipath networks.
    In Computers & Security, Volume 58, 106-124, May 2016.
    [http://www.sciencedirect.com/science/article/pii/S0167404815001960
  11. Chuan Hu and Huiping Cao: Discovering Time-evolving Influence from Dynamic Heterogeneous Graphs.
    In Proc. of IEEE International Conference on Big Data 2015, 2253-2262.
    [PDF] [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7364014].
    The source code for this paper can be downloaded from this github repository.
  12. Yifan Hao, Huiping Cao, Yan Qi, Chuan Hu, Sukumar Brahma, and Jingyu Han: Efficient Keyword Search on Graphs using MapReduce.
    In IEEE International Conference on Big Data 2015, 2871-2873.
    [pdf] [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7364106].
  13. James Obert, Inna Pivkina, Hong Huang, Huiping Cao: Dynamically Differentiated Multipath Security in Fixed Bandwidth Networks. In Military Communications Conference (MILCOM 2014), 88-93. Oct. 6 – 8, 2014. (Acceptance rate: N.A.)
    [http://dx.doi.org/10.1109/MILCOM.2014.22]
  14. Chuan Hu, Huiping Cao, Chaomin Ke: Detecting Influence Relationships from Graphs.
    In Proc. of SIAM Data Mining, SDM 2014:821-829.
    This Link has the paper, source code, data sets, and technical report.
    The source code for this paper can also be downloaded from this github repository.
  15. Jingyu Han, Kejia Chen, Zhiming Ding, Huiping Cao: An efficient location reporting and indexing framework for urban road moving objects. In
    Distributed and Parallel Databases 32(2): 271-311 (2014). [http://link.springer.com/article/10.1007%2Fs10619-013-7135-5]
  16. Yifan Hao, Huiping Cao, Chuan Hu, Kabi Bhattarai, Satyajayant Misra: K-anonymity for social networks containing rich structural and textual information. Social Netw. Analys. Mining 4(1): 222-261, August (2014).
    [http://link.springer.com/article/10.1007%2Fs13278-014-0223-3]
  17. Yifan Hao, Huiping Cao, Kabi Bhattarai, Satyajayant Misra: STK-anonymity: k-anonymity of social networks containing both structural and textual information, In Proc. of DBSocial 2013:19-24, co-located with SIGMOD 2013. (Acceptance rate: N.A.)
    [http://dl.acm.org/citation.cfm?doid=2484702.2484707]
  18. James Obert, Huiping Cao, Hong Huang: Determination of Multipath Security Using Efficient Pattern Matching. In International Journal of Computer Science and Information Security (IJCSIS), 11(11), 24-33 (2013). [http://www.scribd.com/doc/190070743/Determination-of-Multipath-Security-Using-Efficient-Pattern-Matching]
  19. Yangpai Liu, Huiping Cao, Yifan Hao, Peng Han, Xinda Zeng: Discovering Context-aware Influential Objects.
    In Proc. of SIAM Data Mining, SDM 2012:780-791. (Acceptance rate: 27%)
    [http://siam.omnibooksonline.com/2012datamining/data/papers/237.pdf]
  20. Huiping Cao, Shawn Bowers, Mark P. Schildhauer: Database Support for Enabling Data-Discovery Queries over Semantically-Annotated Observational Data. In LNCS Transactions on Large-Scale Data- and Knowledge-Centered Systems (TLDKS), 6: 198-228 (2012). http://link.springer.com/chapter/10.1007%2F978-3-642-34179-3_7
  21. Huiping Cao, K. Selçuk Candan, and Maria Luisa Sapino: Skynets: Searching for Minimum Trees in Graphs with Incomparable Edge Weights. In Proc. of Intl. Conf. on Information and Knowledge Management, CIKM 2011, 1775-1784. (Acceptance rate: 15%) http://dl.acm.org/citation.cfm?doid=2063576.2063833
  22. Huiping Cao, Shawn Bowers, Mark P. Schildhauer: Approaches for Semantically Annotating and Discovering Scientific Observational Data. In Proc. of Intl. Conf. on Database and Expert System Applications, DEXA 2011, 526-541. (Acceptance rate: 25%) http://www.springerlink.com/content/v56047534m051l71/
  23. Shawn Bowers, Huiping Cao, Mark Schildhauer, Matt Jones, Ben Leinfelder, and Margaret O’Brien: A Semantic Annotation Framework for Retrieving and Analyzing Observational Datasets. In the third workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR2010), co-located with Intl. Conf. on Information and Knowledge Management (CIKM), 31-32, 2010. (Acceptance rate: N.A.) http://dl.acm.org/citation.cfm?doid=1871962.1871982
  24. Shawn Bowers, Jay Kudo, Huiping Cao, Mark P. Schildhauer: ObsDB: A System for Uniformly Storing and Querying Heterogeneous Observational Data. In Proc. of the IEEE Intl. Conf. on e-Science, 2010, 261-268. (Acceptance rate: 30%) http://www.computer.org/csdl/proceedings/escience/2010/4290/00/4290a261-abs.html
  25. Huiping Cao, Yan Qi, K. Selçuk Candan, and Maria Luisa Sapino: Feedback-driven result ranking and query refinement for exploring semi-structured data collections. In Proc. of Intl. Conf. on Extending Database Technology, EDBT 2010, 3-14. (Acceptance rate: N.A.) http://dl.acm.org/citation.cfm?doid=1739041.1739046
  26. Huiping Cao, Yan Qi, K. Selçuk Candan, and Maria Luisa Sapino: Exploring Path Query Results through Relevance Feedback. In Proc. of Intl. Conf. on Information and Knowledge Management, CIKM 2009, 1959-1962. (Acceptance rate: N.A.) http://dl.acm.org/citation.cfm?doid=1645953.1646275
  27. K. Selçuk Candan, Huiping Cao, Yan Qi, and Maria Luisa Sapino: AlphaSum: Size-Constrained Table Summarization using Value Lattices. In Proc. of Intl. Conf. on Extending Database Technology, EDBT 2009, 96-107. (Acceptance rate: 32.5%) http://dl.acm.org/citation.cfm?doid=1516360.1516373
  28. K. Selçuk Candan, Huiping Cao, Yan Qi, and Maria Luisa Sapino: System Support for Exploration and Expert Feedback in Resolving Conflicts during Integration of Metadata. In The VLDB Journal, 17(6): 1407-1444, 2008. http://www.springerlink.com/content/e63571635m577344/
  29. K. Selçuk Candan, Huiping Cao, Yan Qi, and Maria Luisa Sapino: Table Summarization with the Help of Domain Lattices. In Proc. of Intl. Conf. on Information and Knowledge Management, CIKM2008, 1473-1474. (Acceptance rate: 16%) http://dl.acm.org/citation.cfm?doid=1458082.1458340
  30. Huiping Cao, Nikos Mamoulis, and David W. Cheung: Discovery of Periodic Patterns in Spatiotemporal Sequences. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 19(4): 453-467, 2007. [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4118704]
  31. Huiping Cao, Nikos Mamoulis, and David W. Cheung: Discovery of Collocation Episodes in Spatiotemporal Data. In Proc. of Intl. Conf. on Data Mining, ICDM2006, 823-827. (Acceptance rate: 10%) http://www.computer.org/csdl/proceedings/icdm/2006/2701/00/270100823-abs.html
  32. Huiping Cao, Nikos Mamoulis, and David W. Cheung: Mining Frequent Spatio-Temporal Sequential Patterns. In Proc. of Intl. Conf. on Data Mining, ICDM2005, 82-89. Received Student Travel award. (Acceptance rate: 13.8%) http://www.computer.org/csdl/proceedings/icdm/2005/2278/00/22780082-abs.html
  33. Nikos Mamoulis, Huiping Cao, George Kollios, Marios Hadjieleftheriou, Yufei Tao, and David W. Cheung: Mining, Indexing, and Querying Historical Spatiotemporal Data. In ACM SIGKDD Proc. of Intl. Conf. on Knowledge Discovery and Data Mining, SIGKDD2004, 236-245. (Acceptance rate: 12%) http://dl.acm.org/citation.cfm?doid=1014052.1014080
  34. Huiping Cao, David W. Cheung, and Nikos Mamoulis: Discovering Partial Periodic Patterns in Discrete Data Sequences. In Proc. of Pacific-Asia Conf. on Knowledge Discovery and Data Mining, PAKDD2004, 653-658. (Acceptance rate: 13%) http://link.springer.com/chapter/10.1007%2F978-3-540-24775-3_77
  35. Yutao Shou, Nikos Mamoulis, Huiping Cao, Dimitris Papadias, and David W. Cheung: Evaluation of Iceberg Distance Joins. In Proc. of Intl. Symp. on Advances in Spatial and Temporal Databases, SSTD2003, 270-288. (Acceptance rate: N.A.) http://link.springer.com/chapter/10.1007%2F978-3-540-45072-6_16
  36. Huiping Cao, Shan Wang, and Lingwei Li: Location Dependent Query in a Mobile Environment. In Journal of Information Sciences, 154(1-2): 71-83, 2003. [http://www.sciencedirect.com/science/article/pii/S0020025503000355