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IJSTR >> Volume 9 - Issue 8, August 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Optimized Neural Network-Based Improved Multiverse Optimizer Algorithm For Automated Arabic Essay Scoring

[Full Text]



Marwa M. Gaheen, Rania M. ElEraky, Ahmed A. Ewees



Automated essay scoring, Natural language processing, Neural network, Multiverse optimizer algorithms, Particle swarm optimization.



The automated essay scoring is recognized as an automatic evaluation of essays or automated essay grading. Such methods are very helpful for assessing human graders and experts when evaluating a large volume of essays. In this paper, a new method is presented to score essays automatically. It uses particle swarm optimization to generate the initial population for the multiverse optimizer algorithm to train the classic Neural Network. It is called pMVO-NN. The proposed method is evaluated using 200 student's essays. These essays are scored by two human experts then they are passed to a pre-processing phase to be prepared and converted to a digit's matrix. The results are evaluated using a set of measures and it is compared with well-known optimization algorithms. The pMVO-NN outperformed all compared algorithms and obtained a correlation equals to 0.987 with the scores of the human experts.



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