Data analytics based techniques for improvement of e-governance in developing nations

lecture at PhD Symposium in 1st International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, 4. 3. 2019, Kurukshetra, India

Rajan Gupta (Author)

Abstract

United Nation’s E-Governance Development Index is a development assessment index for all the nations around on the E-Governance front. Every country is ranked on the basis of a quantitative parameter derived out of few important components. But such development assessment index is missing at regional level in a country so that regional development can be assessed and work can be monitored. Few countries have local assessment models but are not exhaustive enough which can be used for development assessment and further development plan formation. Therefore, there is a need for this study to develop such assessment framework and develop approaches to have a meaningful contribution in improvement of E-Governance in the country at regional level. After the assessment of the regions on the development front of E-Governance, the improvement techniques must be defined for the weak parameters, so that regional development can be enhanced. For the experiment purpose, India has been chosen as the experiment country for which datasets has been used from Indian E-Governance transactions. This problem is important to be addressed because an overall quantitative measure of E-Governance development of the country will help in improving overall E-Governance rankings at world level, attract better investors, and will help the government to prepare a more inclusive plan on the development front. Most of the studies in literature are citizen centric and thus are not fit for development assessment. The current study has not only developed a framework but has also analyzed various components related to it in detail and suggested the way ahead for E-Governance in the country

Keywords

E-Governance;Development Assessment;Location Allocation;Intrusion Detection;

Data

Language:	English
Year of publishing:	2019
Typology:	3.15 - Unpublished Conference Contribution
Organization:	UNG - University of Nova Gorica
UDC:	004
COBISS:	58223619
Views:	1350
Downloads:	0
Average score:	0 (0 votes)
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Other data

URN:	URN:SI:UNG
Type (COBISS):	Not categorized
ID:	12721853