Geospatial data mining techniques to investigate gender equality and empowerment of women status in Bangladesh

  • Authors:
  • Rashedur M. Rahman;Nahida Sultana

  • Affiliations:
  • Department of Electrical Engineering and Computer Science, North South University, Plot-15, Block-B, Bashundhara, Dhaka 1229, Bangladesh;Department of Electrical Engineering and Computer Science, North South University, Plot-15, Block-B, Bashundhara, Dhaka 1229, Bangladesh

  • Venue:
  • International Journal of Knowledge Engineering and Soft Data Paradigms
  • Year:
  • 2013

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Abstract

In this paper we present and investigate geospatial data mining techniques on different data set to investigate how the promotion of gender equality and empowerment of women is carried out throughout Bangladesh. Promoting gender equality and empowerment of women is one of the goals of the Millennium Development Goals of 2015. The indicators of this paper are women literacy rate, ratio of girls in primary, secondary and tertiary education, and employment history in different sectors of Bangladesh. Our aim is to study these indicators, analyse those statistically and geospatially mining those data with respect to different areas of Bangladesh. We also compare the results of spatial regression model with classical regression model on this data. The results demonstrate that spatial lag model outperforms the classical model in different perspectives. We have found that education indicators have a tendency to produce spatial clusters. It is clear that spatial data mining can provide interesting and useful insights for the government, economists and relevant decision makers. The results can also be used for causal analysis by domain experts.