[1] Poel D V, Buckinx W. Predicting online-purchasing behaviour. European Journal of Operational Research, 2005, 166(2):557-575.[2] Wang J, Song S, Zhu X, Lin X. Efficient recovery of missing events. Proceedings of the VLDB Endowment, 2013, 6(10):841-852.[3] Jeung H, Yiu M L, Zhou X, Jensen C S. Path prediction and predictive range querying in road network databases. The International Journal on Very Large Data Bases, 2010, 19(4):585-602.[4] Song R, Sun W, Zheng B, Zheng Y. Press:A novel framework of trajectory compression in road networks. Proceedings of the VLDB Endowment, 2014, 7(9):661-672.[5] Liu C, White R W, Dumais S T. Understanding web browsing behaviors through Weibull analysis of dwell time. In Proc. the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, July 2010, pp.379-386.[6] Dwork C, McSherry F, Nissim K, Smith A. Calibrating noise to sensitivity in private data analysis. In Proc. the 3rd Conference on Theory of Cryptography, March 2006, pp.265-284.[7] Götz M, Nath S, Gehrke J. Maskit:Privately releasing user context streams for personalized mobile applications. In Proc. the 2012 ACM SIGMOD International Conference on Management of Data, May 2012, pp.289-300.[8] He Y, Barman S, Wang D, Naughton J F. On the complexity of privacy-preserving complex event processing. In Proc. the 30th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, June 2011, pp.165-174.[9] Wang D, He Y, Rundensteiner E A, Naughton J F. Utilitymaximizing event stream suppression. In Proc. the 2013 ACM SIGMOD International Conference on Management of Data, June 2013, pp.589-600.[10] Rastogi V, Nath S. Differentially private aggregation of distributed time-series with transformation and encryption. In Proc. the 2010 ACM SIGMOD International Conference on Management of Data, June 2010, pp.735-746.[11] Chen R, Ács G, Castelluccia C. Differentially private se-quential data publication via variable-length n-grams. In Proc. the 2012 ACM conference on Computer and Communications Security, October 2012, pp.638-649.[12] Zeng C, Naughton J F, Cai J. On differentially private frequent itemset mining. Proceedings of the VLDB Endowment, 2012, 6(1):25-36.[13] Hay M, Rastogi V, Miklau G, Suciu D. Boosting the accuracy of differentially private histograms through consistency. Proceedings of the VLDB Endowment, 2010, 3(1):1021-1032.[14] Qardaji W H, Yang W, Li N. Understanding hierarchical methods for differentially private histograms. Proceedings of the VLDB Endowment, 2013, 6(14):1954-1965.[15] Li H G, Chen S, Tatemura J, Agrawal D, Candan K S, Hsiung W P. Safety guarantee of continuous join queries over punctuated data streams. In Proc. the 32nd International Conference on Very Large Data Bases, September 2006, pp.19-30.[16] Maheshwari P, Tam S S L. Events-based exception handling in supply chain management using Web services. In Proc. the Advanced Int. Conference on Telecommunications and Int. Conference on Internet and Web Applications and Services, February 2006, pp.151-156.[17] Roh G P, Roh J W, Hwang S, Yi B K. Supporting patternmatching queries over trajectories on road networks. IEEE Transactions on Knowledge and Data Engineering, 2011, 23(11):1753-1758.[18] Maruseac M, Ghinita G, Rughinis R. Privacy-preserving publication of provenance workflows. In Proc. the 4th ACM Conference on Data and Application Security and Privacy, February 2014, pp.159-162.[19] Chen R, Fung B C M, Desai B C, Sossou N M. Differentially private transit data publication:A case study on the Montreal transportation system. In Proc. the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2012, pp.213-221.[20] McSherry F, Mahajan R. Differentially-private network trace analysis. In Proc. the ACM SIGCOMM 2010 Conference, August 2010, pp.123-134.[21] He X, Cormode G, Machanavajjhala A, Procopiuc C M, Srivastava D. DPT:Differentially private trajectory synthesis using hierarchical reference systems. Proceedings of the VLDB Endowment, 2015, 8(11):1154-1165.[22] Kellaris G, Papadopoulos S. Practical differential privacy via grouping and smoothing. Proceedings of the VLDB Endowment, 2013, 6(5):301-312.[23] Yuan G, Zhang Z, Winslett M, Xiao X, Yang Y, Hao Z. Lowrank mechanism:Optimizing batch queries under differential privacy. Proceedings of the VLDB Endowment, 2012, 5(11):1352-1363.[24] Li C, Miklau G. An adaptive mechanism for accurate query answering under differential privacy. Proceedings of the VLDB Endowment, 2012, 5(6):514-525.[25] Li C, Hay M, Miklau G, Wang Y. A data-and workloadaware query answering algorithm for range queries under differential privacy. Proceedings of the VLDB Endowment, 2014, 7(5):341-352. |