Abstract: Governments around the world generated large data in multitude of formats and received enormous information from citizens, employees , business and other community in wide variety of formats through various channels such as traditional (Post/Fax) and/or modern (Website/Social media).Simply storing this valuable information does not provide any benefits for decision making in planning and formulation of guide lines for new projects.Therefore the government organizations can use enormous data for discovering hidden patterns, previously unknown relationships, extract meaningful information and trends for decision making.The data mining techniques can help in not only to detect fraud and security threats, but also it can be used for measuring influence facts like citizens’ behavior, desire and need, that affect on improving e-government services such as Government to Citizen (G2C), Government to Government (G2G), Government to Employee (G2E) and Government to Business (G2B).
The objective of this paper is how data mining techniques can help the government organizations in decision making from large data, which is collected from various organizations (National, State and Local level).This paper proposes “A Framework for e-Government Data Mining Applications (eGDMA) – for effective Citizen Services”- An Indian Perspective” for empowering e-government services in decision making. In this framework, the government applications are divided into two, namely; Common and Department’s Specific applications. These applications are applied and examined through an exhaustive case study and reported the findings and results. This paper also examined various issues and challenges using Data Mining techniques for decision making within the government organizations.
Keywords: Data Mining, Decision Making, Decision Support System, E-Government, Knowledge Management
Title: A Framework for e-Government Data Mining Applications (eGDMA) for effective Citizen Services -An Indian Perspective
Author: Dr. VELAMALA RANGA RAO
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
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