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Table 1.

A summary of related work.

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Fig 1.

Rules of normalization.

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Fig 2.

The Word2vec models: CBOW and Skip-gram.

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Fig 3.

The proposed system block diagram for automatic grading of short responses.

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Fig 4.

The LSTM cell structure.

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Fig 5.

The LSTM optimization process.

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Table 2.

A sample question, model answer, students’ answers, and grades.

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Table 2 Expand

Table 3.

An English translation of the previous Arabic sample.

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Table 3 Expand

Table 4.

The samples files description.

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Fig 6.

LSTM-GWO prediction and actual scores with experiment 1.

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Fig 7.

LSTM-GWO prediction and actual scores with experiment 2.

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Fig 8.

LSTM-GWO prediction and actual scores with experiment 3.

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Fig 9.

LSTM-GWO prediction and actual scores with experiment 4.

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Fig 10.

LSTM-GWO prediction and actual scores with experiment 5.

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Fig 11.

LSTM-GWO prediction and actual scores with experiment 6.

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Fig 12.

LSTM-GWO prediction and actual scores with experiment 7.

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Fig 13.

LSTM-GWO prediction and actual scores with experiment 8.

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Fig 14.

The LSTM-GWO accuracy and loss with experiment 1.

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Fig 15.

The LSTM-GWO accuracy and loss with experiment 2.

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Fig 16.

The LSTM-GWO accuracy and loss with experiment 3.

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Fig 17.

The LSTM-GWO accuracy and loss with experiment 4.

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Fig 18.

The LSTM-GWO accuracy and loss with experiment 5.

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Fig 19.

The LSTM-GWO accuracy and loss with experiment 6.

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Fig 20.

The LSTM-GWO accuracy and loss with experiment 7.

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Fig 21.

The LSTM-GWO accuracy and loss with experiment 8.

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Fig 22.

Graphical representation of Lesk.

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Table 5.

Comparison of the proposed model and compared models with experiment 1.

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Table 5 Expand

Fig 23.

LSTM-GWO performance evaluation with experiment 1.

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Table 6.

Comparison of the proposed model and compared models with experiment 2.

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Table 6 Expand

Fig 24.

LSTM-GWO performance evaluation with experiment 2.

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Table 7.

Comparison of the proposed model and compared models with experiment 3.

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Fig 25.

LSTM-GWO performance evaluation with experiment 3.

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Table 8.

Comparison of the proposed model and compared models with experiment 4.

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Table 8 Expand

Fig 26.

LSTM-GWO performance evaluation with experiment 4.

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Table 9.

Comparison of the proposed model and compared models with experiment 5.

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Fig 27.

LSTM-GWO performance evaluation with experiment 5.

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Table 10.

Comparison of the proposed model and compared models with experiment 6.

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Fig 28.

LSTM-GWO performance evaluation with experiment 6.

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Table 11.

Comparison of the proposed model and compared models with experiment 7.

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Fig 29.

LSTM-GWO performance evaluation with experiment 7.

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Table 12.

Comparison of the proposed model and compared models with experiment 8.

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Fig 30.

LSTM-GWO performance evaluation with experiment 8.

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Fig 31.

Training time of LSTM-GWO and other models.

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