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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]

 

AUTHOR(S)

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

 

KEYWORDS

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

 

ABSTRACT

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.

 

REFERENCES

[1] Jagdev Bhogal, Andrew MacFarlane, and Peter Smith. A review of ontology based query expansion. Information processing & management, 43(4):866–886, 2007.
[2] ChengXiang Zhai. Statistical language models for information retrieval. Synthesis Lectures on Human Language Technologies, 1(1):1–141, 2008.
[3] Manish Sharma and Rahul Patel. A survey on information retrieval models, techniques and applications. International Journal of Emerging Technology and Advanced Engineering, 3(11):542–545, 2013.
[4] Aqil M Azmi, Maram F Al-Jouie, and Muhammad Hussain. Aaee–automated evaluation of students’ essays in arabic language. Information Processing & Management, 56(5):1736–1752, 2019.
[5] AA Ewees, Mohamed Eisa, and MM Refaat. Comparison of cosine similarity and k-nn for automated essays scoring. International Journal of Advanced Research in Computer and Communication Engineering, 3(12), 2014.
[6] Marwa A Gaheen, Ahmed A Ewees, and Mohamed Eisa. Students head-pose estimation using partiallylatent mixture. In Emerging Trends in Electrical, Communications, and Information Technologies, pages 717–729. Springer, 2020.
[7] Marwa A Gaheen, Ahmed A Ewees, and Fifi Farouk. Face-pose estimation for learning systems. In 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pages 1–6. IEEE, 2019.
[8] Ahmed A Ewees, Hend A ElLaban, and Rania M ElEraky. Features selection for facial expression recognition. In 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pages 1–6. IEEE, 2019.
[9] Frank Hutter, Lars Kotthoff, and Joaquin Vanschoren. Automated machine learning-methods, systems, challenges, 2019.
[10] Khaled Ahmed, Ahmed A Ewees, and Aboul Ella Hassanien. Prediction and management system for forest fires based on hybrid flower pollination optimization algorithm and adaptive neuro-fuzzy inference system. In 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS), pages 299–304. IEEE, 2017.
[11] Liu Penghui, Ahmed A Ewees, Beste Hamiye Beyaztas, Chongchong Qi, Sinan Q Salih, Nadhir Al-Ansari, Suraj Kumar Bhagat, Zaher Mundher Yaseen, and Vijay P Singh. Metaheuristic optimization algorithms hybridized with artificial intelligence model for soil temperature prediction: Novel model. IEEE Access, 8:51884–51904, 2020.
[12] A. A. Bialy, M. A. Gaheen, R. M. ElEraky, A. F. ElGamal, and A. A. Ewees. Single arabic document summarization using natural language processing technique. In In Recent Advances in NLP: The Case of Arabic Language, pages 649–657. Springer, 2020.
[13] Nitin Madnani and Aoife Cahill. Automated scoring: Beyond natural language processing. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1099–1109, 2018.
[14] Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. A convolutional neural network for modelling sentences. arXiv preprint arXiv:1404.2188, 2014.
[15] Zakaria Alameer, Mohamed Abd Elaziz, Ahmed A Ewees, Haiwang Ye, and Zhang Jianhua. Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm. Resources Policy, 61:250–260, 2019.
[16] Ahmed T Sahlol, Yasmine S Moemen, Ahmed A Ewees, and Aboul Ella Hassanien. Evaluation of cisplatin efficiency as a chemotherapeutic drug based on neural networks optimized by genetic algorithm. In 2017 12th International Conference on Computer Engineering and Systems (ICCES), pages 682–685. IEEE, 2017.
[17] Ahmed T Sahlol, Ahmed A Ewees, Ahmed Monem Hemdan, and Aboul Ella Hassanien. Training feedforward neural networks using sine-cosine algorithm to improve the prediction of liver enzymes on fish farmed on nano-selenite. In 2016 12th International Computer Engineering Conference (ICENCO), pages 35–40. IEEE, 2016.
[18] Rie Johnson and Tong Zhang. Effective use of word order for text categorization with convolutional neural networks. arXiv preprint arXiv:1412.1058, 2014.
[19] David Zimbra, Manoochehr Ghiassi, and Sean Lee. Brand-related twitter sentiment analysis using feature engineering and the dynamic architecture for artificial neural networks. In 2016 49th Hawaii International Conference on System Sciences (HICSS), pages 1930–1938. IEEE, 2016.
[20] Nizar Y Habash. Introduction to arabic natural language processing. Synthesis Lectures on Human Language Technologies, 3(1):1–187, 2010.
[21] Wenxin Zhu. A study on the application of automated essay scoring in college english writing based on pigai. In 2019 5th International Conference on Social Science and Higher Education (ICSSHE 2019). Atlantis Press, 2019.
[22] Syed Latifi, Mark J Gierl, Andr´e-Philippe Boulais, and Andr´e F De Champlain. Using automated scoring to evaluate written responses in english and french on a high-stakes clinical competency examination. Evaluation & the health professions, 39(1):100–113, 2016.
[23] Mansour Alghamdi, Mohamed Alkanhal, Mohamed Al-Badrashiny, Abdulaziz Al-Qabbany, Ali Areshey, and Abdulaziz Alharbi. A hybrid automatic scoring system for arabic essays. Ai Communications, 27(2):103–111, 2014.
[24] Ayad R Abbas and Ahmed S Al-qazaz. Automated arabic essay scoring (aaes) using vectors space model (vsm) and latent semantics indexing (lsi). Engineering and Technology Journal, 33(3 Part (B) Scientific):410–426, 2015.
[25] Kaveh Taghipour and Hwee Tou Ng. A neural approach to automated essay scoring. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1882–1891, 2016.
[26] Seyedali Mirjalili, Seyed Mohammad Mirjalili, and Abdolreza Hatamlou. Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Computing and Applications, 27(2):495–513, 2016.
[27] Ahmed A Ewees, Mohamed Abd El Aziz, and Aboul Ella Hassanien. Chaotic multi-verse optimizerbased feature selection. Neural Computing and Applications, 31(4):991–1006, 2019.
[28] Mohamed Abd Elaziz, Diego Oliva, Ahmed A Ewees, and Shengwu Xiong. Multi-level thresholdingbased grey scale image segmentation using multi-objective multi-verse optimizer. Expert Systems with Applications, 125:112–129, 2019.
[29] Scott Deerwester, Susan T Dumais, GeorgeWFurnas, Thomas K Landauer, and Richard Harshman. Indexing by latent semantic analysis. Journal of the American society for information science, 41(6):391–407, 1990.
[30] Thomas K Landauer, Peter W Foltz, and Darrell Laham. An introduction to latent semantic analysis. Discourse processes, 25(2-3):259–284, 1998.
[31] Tuomo Kakkonen and Erkki Sutinen. Automatic assessment of the content of essays based on course materials. In ITRE 2004. 2nd International Conference Information Technology: Research and Education, pages 126–130. IEEE, 2004.
[32] Haydee Melo and Junzo Watada. Gaussian-pso with fuzzy reasoning based on structural learning for training a neural network. Neurocomputing, 172:405–412, 2016.
[33] Abdulaziz Shehab, Mahmoud Faroun, and Magdi Rashad. An automatic arabic essay grading system based on text similarity algorithms. International Journal of Advanced Computer Science and Applications (IJACSA), 9(3):263–268, 2018