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WorldCist'17 - 5th World Conference on Information Systems and Technologies

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A Feature Selection Application using Particle Swarm Optimization for Learning Concept Detection

Recent developments of computational intelligence on educational technology yield concept map mining as a new research area. Concept map mining covers the extraction of learning concepts, specifying relations among them, and generating a concept map from educational contents. In this study, we focused on determining the features that characterizes a learning concept extracted from an educational text as raw data. The first three features are detected by using a hybrid system of Multi Layer Perceptron (MLP) and Particle Swarm Optimization (PSO),
and the performance of the applied method is gauged in the viewpoint of a typical classification problem.

Author(s):

Korhan Günel    
Adnan Menderes University
Turkey

Kazım Erdoğdu    
Yaşar University
Turkey

Refet Polat    
Yaşar University
Turkey

Yasin Özarslan    
Yaşar University
Turkey

 

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