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Data Mining of World Bank Indicators

In: Strategic Innovative Marketing

Author

Listed:
  • Maha A. Hana

    (Canadian International College (deputed from Department of Information Systems, Faculty of Computers and Information, Helwan University))

Abstract

World Bank annual report contains vital data indicators about many countries. Data mining techniques helps in studying the underlying relation between different indicators. This research proposes a clustering system for Egypt’s World Bank indicators. The proposed system has three phases; preprocessing phase, clustering phase and analysis phase. Preprocessing phase consolidates Egypt’s data and prepares it for clustering. Clustering phase estimates the appropriate number of clusters and uses K-Means to cluster both years’ data and indicators data values. Analysis phase uses principle component analysis to find the most important indicators for each type of cluster. The results indicate that years’ clusters are more compact and separated than indicators’ clusters.

Suggested Citation

  • Maha A. Hana, 2017. "Data Mining of World Bank Indicators," Springer Proceedings in Business and Economics, in: Androniki Kavoura & Damianos P. Sakas & Petros Tomaras (ed.), Strategic Innovative Marketing, pages 521-527, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-56288-9_69
    DOI: 10.1007/978-3-319-56288-9_69
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