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EDBT
2016
ACM

On-Line Mobility Pattern Discovering using Trajectory Data

4 years 7 months ago
On-Line Mobility Pattern Discovering using Trajectory Data
Mobile location tracking becomes ubiquitous in many applications, which raises great interests in trajectory data analysis and mining. Most existing work tackled the problem of offline trajectory pattern mining. Dynamic discovery and updates of patterns in trajectory data streams in (quasi) real time is a more complex task. In this paper, we propose an incremental algorithm to solve this problem, while maintaining the evolution of the patterns as well as the membership of the moving objects to their patterns.
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where EDBT
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