Comparison of Decision Tree and Naïve Bayes Methods in Classification of Researcher’s Cognitive Styles inAcademic Environment
Publish place: Journal of Advances in Computer Research، Vol: 3، Issue: 2
Publish Year: 1391
Type: Journal paper
Language: English
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Index date: 6 September 2016
Comparison of Decision Tree and Naïve Bayes Methods in Classification of Researcher’s Cognitive Styles inAcademic Environment abstract
In today world of internet, it is important to feedback the users based on whatthey demand. Moreover, one of the important tasks in data mining is classification.Today, there are several classification techniques in order to solve the classificationproblems like Genetic Algorithm, Decision Tree, Bayesian and others. In thisarticle, it is attempted to classify researchers to Expert and Novice based oncognitive style factors in order to have as best as possible answers. The domain ofthis research is based on academic environment. The critical point of this study is toclassify the researchers based on Decision Tree and Naïve Bayes techniques andfinally select the best method based on the highest accuracy of each method to helpthe researchers to have the best feedback based on their demands in the digitallibraries
Comparison of Decision Tree and Naïve Bayes Methods in Classification of Researcher’s Cognitive Styles inAcademic Environment Keywords:
Comparison of Decision Tree and Naïve Bayes Methods in Classification of Researcher’s Cognitive Styles inAcademic Environment authors
Zahra Nematzadeh Balagatabi
Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran