A study of comparative clustering of EU countries using the DBSCAN and k-means techniques within the theoretical framework of systemic geopolitical analysis. (2017)

• Record Type: Journal Article
• Authors: Savvas, Ilias K.; Stogiannos, Alekos; Mazis, Ioannis Th.
• Is Part Of: International journal of grid and utility computing. Volume 8:Number 2(2017)
• Page Start: 94
• Page End: 108
• Publication Date: 2017
• Subjects: systemic geopolitics -- data mining -- MPI -- parallel k-means -- DBSCAN; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

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.