[conference]
In recent years, the constant increase of waterway traffic generates a high volume of AIS data that require a big effort to be processed and analyzed in near real-time. In this paper, we analyze an AIS data set and we propose a data reduction technique that can be applied on AIS data without losing any important information in order to reduce it to a manageable size data set that can be further used for analysis or can be easily used for AIS data visualization applications.
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