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The EVAS Model:Solving E-Voting Problems in Nigeria


Affiliations
1 Department of Computer Science, University of Agriculture, Abeokuta, Nigeria
2 Department of Computer & Information Science, Tai Solarin Univeristy of Education, IJebu-Ode, Nigeria
3 Department of Computer Science, University of Nottingham, United Kingdom
 

E-voting is said to have a lot of loop holes. Solving these problems first starts with their definition as either technical or procedural. In this paper we look at the problem from the procedure perspective and we identify some issues that previous models do not cater for. The model we proposed allows for high-level monitoring of the balloting process and takes advantage of the semantic search process to ensure security of the e-voting procedures through over-the-board authentication. The model also solves the old problem of recounting of the ballots/votes.

Keywords

Visual Analytics, Sematic Search, Natural Language Processing, E-Voting, Machine Learning.
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  • The EVAS Model:Solving E-Voting Problems in Nigeria

Abstract Views: 231  |  PDF Views: 0

Authors

O. S. Ogunseye
Department of Computer Science, University of Agriculture, Abeokuta, Nigeria
O. Folorunso
Department of Computer Science, University of Agriculture, Abeokuta, Nigeria
J. O. Okesola
Department of Computer & Information Science, Tai Solarin Univeristy of Education, IJebu-Ode, Nigeria
J. R. Woodward
Department of Computer Science, University of Nottingham, United Kingdom

Abstract


E-voting is said to have a lot of loop holes. Solving these problems first starts with their definition as either technical or procedural. In this paper we look at the problem from the procedure perspective and we identify some issues that previous models do not cater for. The model we proposed allows for high-level monitoring of the balloting process and takes advantage of the semantic search process to ensure security of the e-voting procedures through over-the-board authentication. The model also solves the old problem of recounting of the ballots/votes.

Keywords


Visual Analytics, Sematic Search, Natural Language Processing, E-Voting, Machine Learning.