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Data Reduction Techniques Applied on Automatic Identification System Data

  • Claudia Ifrim
  • Iulian Iuga
  • Florin Pop
  • Manolis WallaceEmail author
  • Vassilis Poulopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10546)

Abstract

In recent years, the constant increase of waterway traffic generates a high volume of Automatic Identification System data that require a big effort to be processed and analyzed in near real-time. In this paper, we analyze an Automatic Identification System data set and we propose a data reduction technique that can be applied on Automatic Identification System 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 Automatic Identification System data visualization applications.

Keywords

AIS data Data reduction techniques Data analysis AIS data visualization Intelligent transport systems 

Notes

Acknowledgments

This work has been partially supported by COST Action IC1302: Semantic keyword-based search on structured data sources (KEYSTONE); we particularly acknowledge the support of the grant COST-STSM-IC1302-36978: “Curating Data Analysis Workflows for Better Workflow Discovery”.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Claudia Ifrim
    • 1
  • Iulian Iuga
    • 2
  • Florin Pop
    • 1
  • Manolis Wallace
    • 3
    Email author
  • Vassilis Poulopoulos
    • 3
  1. 1.Faculty of Automatic Control and Computers Computer Science DepartmentUniversity Politehnica of BucharestBucharestRomania
  2. 2.BucharestRomania
  3. 3.Knowledge and Uncertainty Research Laboratory Department of Informatics and TelecommunicationsUniversity of the PeloponneseTripolisGreece

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