Title: A study of comparative clustering of EU countries using the DBSCAN and k-means techniques within the theoretical framework of systemic geopolitical analysis

Authors: Ilias K. Savvas; Alekos Stogiannos; Ioannis Th. Mazis

Addresses: Department of Computer Science and Engineering, T.E.I. of Thessaly, Larissa, Greece ' Faculty of Turkish and Modern Asian Studies, National and Kapodistrian University of Athens, Greece ' Faculty of Turkish and Modern Asian Studies, National and Kapodistrian University of Athens, Greece

Abstract: As a geographical method of analysing power redistribution, Systemic Geopolitical Analysis (according to Ioannis Th. Mazis theoretical basis) proposes a multi-dimensional, interdisciplinary research pattern, which embraces economic, cultural, political and defensive facts. The amount of data produced combining these attributes is extremely large and complex. One of the solutions to explore and analyse this data is clustering it. In this work, two clustering algorithms were used, namely DBSCAN and the k-means techniques both of which cluster data according to its characteristics. While DBSCAN groups data based on the minimum size of participating objects per cluster and the minimum required distance between them, k-means clusters the data objects according the pre-desired number of groups. Thus, since the two methods use different roads to group the data objects, they form different clusters but each one has its importance depending on the characteristics of the applied method. As a result, in this work a comparative study is presented.

Keywords: systemic geopolitics; data mining; MPI; parallel k-means; DBSCAN.

DOI: 10.1504/IJGUC.2017.085911

International Journal of Grid and Utility Computing, 2017 Vol.8 No.2, pp.94 - 108

Received: 04 Nov 2015
Accepted: 28 Feb 2016
Published online: 18 Aug 2017 *

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