The recent advances in technologies for mobile devices, like GPS and mobile phones, are generating large amounts of a new kind of data: trajectories of moving objects. These data are normally available as sample points, with very little or no semantics. Trajectory data can be used in a variety of applications, but the form as the data are available makes the extraction of meaningful patterns very complex from an application point of view. Several data preprocessing steps are necessary to enrich these data with domain information for data mining. In this chapter,we present a general framework for context-aware trajectory data mining. In this framework we are able to enrich trajectories with additional geographic information that attends the application requirements. We evaluate the proposed framework with experiments on real data for two application domains: traffic management and an outdoor game.
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Bogorny, V., Wachowicz, M. (2009). A Framework for Context-Aware Trajectory. In: Cao, L., Yu, P.S., Zhang, C., Zhang, H. (eds) Data Mining for Business Applications. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-79420-4_16
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DOI: https://doi.org/10.1007/978-0-387-79420-4_16
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