Mining and Learning from Moving Objects Databases
Abstract: We work on the following topics.
Similarity Search for Multi-dimensional Trajectories
Similarity/Metric Learning for Multi-dimensional Trajectories
Indexing Spatio-Temporal Continuous Trajectory for Fast Data Retrieval
Grant:
NASA ROSES-2008 (Advanced Information Systems Technology, "Moving Objects Database for Weather Event Analysis and Tracking", PI: Markus Schneiders (U. Florida, Gainesville); Co-I/Science-PI: Shen-Shyang Ho; W. Timothy Liu., 1 May 2009-30 Apr. 2012.
Project Demo (University of Florida):
Moving Objects Database for East Pacific/North Atlantic Hurricane Trajectories from 1970 to 2009.
References:
(NEW) M. Schneider, S.-S. Ho, M. Agrawal, T. Chen, H. Liu, G. Viswanathan, A Moving Objects Database Infrastructure for Hurricane Research: Data Integration and Complex Object Management, Earth Science Technology Forum, June 21-23, 2011.
S.-S. Ho, W. Tang, and W. T. Liu, Tropical Cyclone Event Sequence Similarity Search via Dimensionality Reduction and Metric Learning, accepted by 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, July 25-28, 2010.
S.-S. Ho, W. Tang, W. T. Liu, and M. Schneider, A Framework for Moving Sensor Data Query and Retrieval for Dynamic Atmospheric Events, accepted by 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany, Jun 30-July 2, 2010.
M. Schneider, S.-S. Ho, T. Chen, A. Khan, G Viswanathan, W. Tang, and W. T. Liu, Moving Objects Database Technology for Ad-Hoc Querying and Satellite Data Retrieval of Dynamic Atmospheric Events, 2010 Earth Science Technology Forum, June 22-24, Arlington, VA, 2010.