2007 TrajectoryPatternMining

• (Giannotti et al., 2007) ⇒ Fosca Giannotti, Mirco Nanni, Fabio Pinelli, and Dino Pedreschi. (2007). “Trajectory Pattern Mining.” In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge discovery and data mining. ISBN:978-1-59593-609-7 doi:10.1145/1281192.1281230

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Abstract

The increasing pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) is leading to the collection of large spatio-temporal datasets and to the opportunity of discovering usable knowledge about movement behaviour, which fosters novel applications and services. In this paper, we move towards this direction and develop an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects. We introduce trajectory patterns as concise descriptions of frequent behaviours, in terms of both space (i.e., the regions of space visited during movements) and time (i.e., the duration of movements). In this setting, we provide a general formal statement of the novel mining problem and then study several different instantiations of different complexity. The various approaches are then empirically evaluated over real data and synthetic benchmarks, comparing their strengths and weaknesses.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2007 TrajectoryPatternMining	Fabio Pinelli Fosca Giannotti Mirco Nanni Dino Pedreschi			Trajectory Pattern Mining				10.1145/1281192.1281230		2007