E-government is important for national development. However, the significant features for E-government stages have not been analyzed intelligently. This research proposes a method, clustering features for rankings (CFR), to find stages and features for E-government. The results show that the adult literacy is significant for the beginning stage and the gross enrollment in education for the mature stage. Technically, dominance-based rough set approach is used to generate criteria's evidential weights of nations' rankings and rough set is then used to identify the clustering features composed of dependency rules. The rules comprise the most relevant and important criteria and the ranking intervals as the intelligent knowledge.
CITATION STYLE
Ko, Y. C., & Fujita, H. (2014). An approach of clustering features for ranked nations of E-government 2012. Acta Polytechnica Hungarica, 11(6), 5–21. https://doi.org/10.12700/aph.11.06.2014.06.1
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