A Framework to Enhance Classification Accuracy for Web Learning System

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Provided by: International Journal of Computer Science and Telecommunications
Topic: Mobility
Format: PDF
In this paper, a framework for cognitive based adaptive Web learning system is presented. It focuses on users' cognitive learning process and activities, as well as the technology support needed. This paper applies data mining algorithms and neural network-based classification algorithms. To develop an effective Web learning system, learner's cognition and cognitive load should be considered. Individualized web learning system is necessary to improve the learning activities. Particle swarm optimization has many advantages then the other genetic algorithm. Particle swarm optimization has more effective classification accuracy than the genetic algorithm.
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