Title: Mining maritime schedules for analysing global shipping networks

Authors: Deepen Doshi; Baljeet Malhotra; Stéphane Bressan; Jasmine Siu Lee Lam

Addresses: School of Computing, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 117590, Singapore ' SAP Research, 30 Pasir Panjang Road, #03-32 Mapletree Business City, Singapore 117440, Singapore ' Centre for Maritime Studies and School of Computing, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 117590, Singapore ' School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore

Abstract: Shipping plays a vital role as trade facilitator in providing cost-efficient transportation. The International Maritime Organisation (IMO) reports that over 90% of the world trade volume is carried by merchant ships. The analysis of shipping networks therefore can create invaluable insight into global trade. In this paper we study the appropriateness of various graph centrality measures to rate, compare and rank ports from various perspectives of global shipping networks. In particular, we illustrate the potential of such analysis on the example of shipping networks constructed from the schedules, readily available on the World Wide Web, of six shipping companies that transport 35-40% of the total volume traded (in TEUs) worldwide.

Keywords: graphs; shipping networks; ports; maritime schedules; data mining; algorithms; measurement; port ranking; scheduling; liner companies; liners.

DOI: 10.1504/IJBIDM.2012.049554

International Journal of Business Intelligence and Data Mining, 2012 Vol.7 No.3, pp.186 - 202

Published online: 12 Nov 2014 *

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