Abstract
Lately, the amount of mobility data recorded by GPS-enabled (and other) devices has increased drastically, entailing the necessity of efficient processing and analysis methods. In many cases, not only the geographic position, but also additional information according to the purpose of the evaluation are traced and/or generated. In this paper, we present an application of a framework for analyzing datasets with several time-dependent attributes. This can be considered as a major extension of our previous work, a comprehensive framework for pattern matching on symbolic trajectories. For an efficient processing of different data types, a variable number of corresponding index types are applied. We demonstrate the expressiveness and efficiency with the help of a sophisticated pattern and a dataset consisting of GPS-recorded animal data and additional geological and meteorological information.
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