JOURNAL PUBLICATIONS AND BOOK CHAPTERS
Adhikari, R., Mutual Association Based Nonlinear Ensemble Mechanism for Time Series Forecasting, Applied Intelligence, vol. 43, no. 2, Sept. 2015.
Aghabozorgi, S. and T.Y. Wah, Clustering of Large Time Series Datasets, Intelligent Data Analysis, vol. 18, no. 5, September 2014.
Akrout, B. and W. Mahdi, Spatio-Temporal Features for the Automatic Control of Driver Drowsiness State and Lack of Concentration, Machine Vision and Applications, vol. 26, no. 1, January 2015.
Al-Naymat, G., Mitigating the Influence of the Curse of Dimensionality on Time Series Similarity Measures, International Journal of Computer Applications in Technology, vol. 52, August 2015.
Begum, N. and E. Keogh, Rare Time Series Motif Discovery From Unbounded Streams, Proceedings of the VLDB Endowment Journal, vol. 8, October 2014.
Chen, H. et al., A Patent Time Series Processing Component for Technology Intelligence
by
Trend
Identification
Functionality,
Neural
Computing
and
Applications, vol. 26, no. 2, February 2015.
Chaiwanarom, P.and C.Lursinsap, Collabarator Recommendation in Interdisciplinary Computer Science Using Degrees of Collaborative Forces, Temporal Evolution of Research Interest, and Comparative Seniority Status, Knowledge-Based Systems, vol. 75, issue C, February 2015.
Campos, R et al., Survey of Temporal Information Retrieval and Related Applications, Computing Surveys (CSUR), vol. 47, no. 2, January 2015.
Gong, D. et al., Structured Time Series Analysis for Human Action Segmentation and Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, July 2014.
Hills, J. et al., Classification of Time Series by Shapelet Transformation, Data Mining and Knowledge Discovery, vol. 28, no. 4, July 2014.
Jeong, Y.S. and R. Jayaraman, Support Vector-based Algorithms with Weighted Dynamic Time Warping Kernel Function for Time Series Classification, vol. 75, issue C, Feb. 2015.
Kim, D. et al., A Spatio-temporal Trend Detection and Related Keywords Recommendation Scheme, Multimedia Systems, vol. 21, no. 1, February 2015.
Li, H., Accurate and Efficient Classification Based on Common Principal Component Analysis for Multivariate Time Series, Neurocomputing, vol. 171, issue C, January 2016.
Pan, J. N. et al., Prediction of Energy’s Environmental Impact Using a ThreeVariable Time Series Model, Expert Systems with Applications: An International Journal, vol. 41, March 2014.
Tanaka, M. and S. Kurahashi, An Analysis of Customer Retention Rates by Time Series Data Mining, International Journal of Computer Applications in Technology, vol. 52, no. 2/3, Sept. 2015.
Tran, H. D., N. Muttil, B. J. C. Perera, Selection of Significant Input Variables for Time Series Forecasting, Environmental Modeling & Software, vol. 64, February 2015.
Xue, X. et al., Trajectory-Based Detection of Urban Expansion Using Landsat Time Series, International Journal of Remote Sensing, vol. 35, no. 4, February 2014.
CONFERENCE PUBLICATIONS
Allard, T. et al., Chiaroscuro: Transparency and Privacy for Massive Personal Time Series Clustering, Proceedings of the ACM SIGMOD International Conference on Management of Data, May 2015.
Chen, L. et al., Flu Gone Viral: Syndromic Surveillance of Flu on Twitter Using Temporal Topic Models, Proceedings of the IEEE International Conference on Data Mining, December 2014.
Liu, G. et al., Discovering Temporal Retweeting Patterns for Social Media Marketng Campaigns, Proceedings of the IEEE International Conference on Data Mining, December 2014.
Luo, C. et al., Correlating Events with Time Series for Incident Diagnosis, Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2014.
