Oriental Journal of Computer Science and Technology

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Mining Intelligent e-Voting Data:A Framework


Affiliations
1 Department of Computer & Information Sciences, Tai Solarin University of Education, Ijebu-Ode, Ogun State, Nigeria
2 Department of Computer Science, University of Agriculture, Abeokuta, Ogun State, Nigeria
 

Intelligent e-voting data has been shown to pose a lot of benefit to e-voting especially in the area of security and recounting. After the election and balloting processes, valuable knowledge can still be extracted from this data. This work provides a framework model as roadmap for developers to follow in future development of such a system. The Perl based sample tested showed optimum performance and hence proves the viability of the methodology.

Keywords

Text Mining, e-Voting, Knowledge Extraction, Data Mining, Semantic Data, Tree Traversal.
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  • Mining Intelligent e-Voting Data:A Framework

Abstract Views: 236  |  PDF Views: 0

Authors

Julius O. Okesola
Department of Computer & Information Sciences, Tai Solarin University of Education, Ijebu-Ode, Ogun State, Nigeria
Oluwafemi S. Ogunseye
Department of Computer Science, University of Agriculture, Abeokuta, Ogun State, Nigeria
Kazeem I. Rufai
Department of Computer & Information Sciences, Tai Solarin University of Education, Ijebu-Ode, Ogun State, Nigeria
Olusegun Folorunso
Department of Computer Science, University of Agriculture, Abeokuta, Ogun State, Nigeria

Abstract


Intelligent e-voting data has been shown to pose a lot of benefit to e-voting especially in the area of security and recounting. After the election and balloting processes, valuable knowledge can still be extracted from this data. This work provides a framework model as roadmap for developers to follow in future development of such a system. The Perl based sample tested showed optimum performance and hence proves the viability of the methodology.

Keywords


Text Mining, e-Voting, Knowledge Extraction, Data Mining, Semantic Data, Tree Traversal.