Mining Spatio-Temporal Patterns in Trajectory Data

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Mining Spatio-Temporal Patterns in Trajectory Data
Spatio-temporal patterns extracted from historical trajectories of moving objects reveal important knowledge about movement behavior for high quality LBS services. Existing approaches transform trajectories into sequences of location symbols and derive frequent subsequences by applying conventional sequential pattern mining algorithms. However, spatio-temporal correlations may be lost due to the inappropriate approximations of spatial and temporal properties. In this paper, we address the problem of mining spatio-temporal patterns from trajectory data. The inefficient description of temporal information decreases the mining efficiency and the interpretability of the patterns. We provide a formal statement of efficient representation of spatio-temporal movements and propose a new approach to discover spatio-temporal patterns in trajectory data. The proposed method first finds meaningful spatio-temporal regions and extracts frequent spatio-temporal patterns based on a prefix-projection a...
Juyoung Kang 0002, Hwan-Seung Yong
Added 19 May 2011
Updated 19 May 2011
Type Journal
Year 2010
Where JIPS
Authors Juyoung Kang 0002, Hwan-Seung Yong
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