Non-separable Transforms for Clustering Trajectories

  • Alfredo Cuzzocrea
  • Elio Masciari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6882)

Abstract

Trajectory data refer to time and position of moving objects generated by different sources using a wide variety of technologies (e.g., RFID tags, GPS, GSM networks). Mining such amounts of data is challenging, since the possibility to extract useful information from these peculiar kind of data is crucial in many application scenarios such as vehicle traffic management, hand-off in cellular networks and supply chain management. In this paper, we address the problem of trajectory data streams clustering, that revealed really challenging as we deal with data (trajectories) for which the order of elements is relevant. We propose a complete framework starting from data preparation task that allows us to make the mining step quite effective. Since the validation of data mining approaches has to be experimental we performed several tests on real world datasets that confirmed the efficiency and effectiveness of the proposed techniques.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alfredo Cuzzocrea
    • 1
  • Elio Masciari
    • 1
  1. 1.ICAR-CNR – Institute of Italian National Research CouncilItaly

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