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Modelling of e-Governance Framework for Mining Knowledge from Massive Grievance Redressal Data
Author(s) -
G Sangeetha,
Lila Rao
Publication year - 2017
Publication title -
international journal of advances in applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2722-2594
pISSN - 2252-8814
DOI - 10.11591/ijaas.v6.i1.pp32-41
Subject(s) - grievance , corporate governance , computer science , process (computing) , data science , world wide web , data mining , business , political science , law , operating system , finance
With the massive proliferation of online applications for the citizens with abundant resources, there is a tremendous hike in usage of e-governance platforms. Right from entrepreneur, players, politicians, students, or anyone who are highly depending on web-based grievance redressal networking sites, which generates loads of massive grievance data that are not only challenging but also highly impossible to understand. The prime reason behind this is grievance data is massive in size and they are highly unstructured. Because of this fact, the proposed system attempts to understand the possibility of performing knowledge discovery process from grievance Data using conventional data mining algorithms. Designed in Java considering massive number of online e-governance framework from civilian’s grievance discussion forums, the proposed system evaluates the effectiveness of performing datamining for Big data.

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