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Spatio-Temporal Data Stream Clustering

  • Zdravko GalićEmail author
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

Spatio-temporal data streams are huge amounts of data pertaining to time and position of moving objects. Mining such amount of data is a challenging problem, since the possibility to extract useful information from this peculiar kind of data is crucial in many RFIP application scenarios. Moreover, spatio-temporal data streams pose interesting challenges for their proper representation, thus making the mining process harder than for classical data. In this chapter we deal with a specific spatio-temporal data stream class, namely trajectory streams that collect data pertaining to spatial and temporal position of mobile objects.

Keywords

Knowledge discovery Spatio-temporal data streams Data stream clustering Trajectory streams Trajectory clustering 

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Copyright information

© The Author(s) 2016

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia

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