1,191
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Hybrid Attention-based Approach for Arabic Paraphrase Detection

ORCID Icon &
Pages 1271-1286 | Received 05 Feb 2021, Accepted 27 Aug 2021, Published online: 05 Sep 2021

References

  • Abdellaoui, H., and M. Zrigui. 2018. Using tweets and emojis to build TEAD: An Arabic dataset for sentiment analysis. Computación y Sistemas 22 (3):777–86. doi:https://doi.org/10.13053/cys-22-3-3031.
  • Alrabiah, M., A. Alsalman, E. Atwell, and N. Alhelewh. 2014. KSUCCA: A key to exploring Arabic historical linguistics. International Journal of Computational Linguistics (IJCL) 5 (2):27–36.
  • Alzahrani, S. 2015. Arabic plagiarism detection using word correlation in N-Grams with K-overlapping approach. In Working Notes for PAN-ArabPlagDet at FIRE, 123–25. Gandhinagar.
  • Alzahrani, S., and N. Salim. 2008. Plagiarism detection in Arabic scripts using fuzzy information retrieval. In Student Conference on Research and Development, 281–85. Johor Bahru, Malaysia.
  • Alzahrani, S., and N. Salim. 2010. Fuzzy semantic-based string similarity for extrinsic plagiarism detection Lab report for PAN at CLEF 2010. In Conference on Multilingual and Multimodal Information Access Evaluation. Padua.
  • Batita, M. A., and M. Zrigui. 2018. Derivational relations in Arabic wordnet. In 9th Global WordNet Conference (GWC), 137–44. Singapore.
  • Bsir, B., and M. Zrigui. 2018. Enhancing deep learning gender identification with gated recurrent units architecture in social text. Computación y Sistemas 22 (3):757–66. doi:https://doi.org/10.13053/cys-22-3-3036.
  • Cosma, G. 2011. An approach to source-code plagiarism detection and investigation using latent semantic analysis. IEEE Transactions on Computers 61 (3):379–94. doi:https://doi.org/10.1109/TC.2011.223.
  • Dey, R., and M. S. Fathi. 2017. Gate-variants of gated recurrent unit (GRU) neural networks. In IEEE 60th international midwest symposium on circuits and systems (MWSCAS), 1597–600. USA.
  • Du, J., L. Gui, and R. Xu. 2017. A convolutional attentional neural network for sentiment classification. In International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), Shenzhen, China, 445–50.
  • Ezzikouri, H., M. Errital, and M. Oukessou. 2017. Fuzzy-semantic similarity for automatic multilingual plagiarism detection. International Journal of Advanced Computer Science and Applications (IJACSA) 8 (9):86–90.
  • Haffar, N., E. Hkiri, and M. Zrigui. 2020. Enrichment of Arabic TimeML corpus. In International Conference on Computational Collective Intelligence (ICCCI), 655–67. Da Nang, Vietnam.
  • He, H., K. Gimpel, and J. Lin. 2015. Multi-perspective sentence similarity modeling with convolutional neural networks. In Conference on empirical methods in natural language processing, 1576–86. Pennsylvania.
  • Hkiri, E., S. Mallat, and M. Zrigui. 2020. Semantic and contextual enrichment of Arabic query leveraging NLP resources and association rules model. International Business Information Management Association (IBIMA), Granada, Spain.
  • Johnson, R., and Z. Tong. 2014. Effective use of word order for text categorization with convolutional neural networks. arXiv Preprint arXiv 1412:1058.
  • Ma, C., P. Kang, B. Wu, Q. Wang, and X. Liu. 2019. Gated attentive-autoencoder for content-aware recommendation. In 12th ACM International Conference on Web Search and Data Mining, 519–27. Australia.
  • Mahmoud, A., and M. Zirgui. 2017. Semantic similarity analysis for paraphrase identification in Arabic texts. In 31st Pacific Asia Conference on Language, Information and Computation (PACLIC), 274–81. Philippine.
  • Mahmoud, A., and M. Zrigui. 2018. Artificial method for building monolingual plagiarized Arabic corpus. Computacion Y Systemas 22 (3):767–76.
  • Mahmoud, A., and M. Zrigui. 2019. Sentence embedding and convolutional neural network for semantic textual similarity detection in Arabic language. Arabian for Engineering and Science Journal 44 (11):9263–74. doi:https://doi.org/10.1007/s13369-019-04039-7.
  • Mahmoud, A., and M. Zrigui. 2021a. Semantic similarity analysis for corpus development and paraphrase detection in Arabic. International Arab Journal of Information Technology (IAJIT) 18 (1):1–7.
  • Mahmoud, A., and M. Zrigui. 2021b. BLSTM-API: Bi-LSTM recurrent neural network-based approach for Arabic paraphrase identification. Arabian for Engineering and Science Journal 46 (4):4163–74. doi:https://doi.org/10.1007/s13369-020-05320-w.
  • Maraoui, M., N. Terbeh, and M. Zrigui. 2018. Arabic discourse analysis based on acoustic, prosodic and phonetic modeling: Elocution evaluation, speech classification and pathological speech correction. International Journal of Speech Technology 21 (4):1071–90. doi:https://doi.org/10.1007/s10772-018-09566-6.
  • Mueller, J., and T. Aditya. 2016. Siamese recurrent architectures for learning sentence similarity. In AAAI Conference on Artificial Intelligence, 2786–92. Arizona USA.
  • Nagoudi, E. B., A. Khorsi, H. Cherroun, and D. Schwab. 2018. A two-level plagiarism detection system for Arabic documents. Cybernetics and Information Technologies 18 (1):1–17. In Press.
  • Pontes, E. L., S. Huet, A. C. Linhares, and J. Torres-Moreno. 2018. Predicting the semantic textual similarity with Siamese CNN and LSTM. arXiv E-prints10641 1810 (3):1810.
  • Saad, M., and W. Ashour. 2010. OSAC: Open source Arabic corpora. In 6th ArchEng Internaional Symposiums on Electrical and Electronics Egineering and Computer Science (EEECS), 1–6. Lefke, North Cyprus.
  • Shajalal, M., and M. Aono. 2018. Semantic textual similarity in Bengali text. In International Conference on Bangla Speech and Language Processing (ICBSLP), 1–5. New Jersey.
  • Ullah, F., J. Wang, M. Farhan, S. Jabbar, Z. Wu, and S. Khalid. 2020. Plagiarism detection in students’ programming assignments based on semantics: Multimedia e-learning based smart assessment methodology. Multimedia Tools and Applications 79 (13–14):8581–98. doi:https://doi.org/10.1007/s11042-018-5827-6.
  • Xie, C., X. Wang, C. Qian, and M. Wang. 2020. A source code similarity based on Siamese neural network. Applied Sciences 10 (21):1–12. doi:https://doi.org/10.3390/app10217519.
  • Yao, L., Z. Pan, and H. Ning. 2019. Unlabeled short text similarity with LSTM encoder. IEEE Access 7 (1):3430–37. doi:https://doi.org/10.1109/ACCESS.2018.2885698.
  • Zuo, F., X. Li, P. Young, L. Luo, Q. Zeng, and Z. Zhang. 2018. Neural machine translation inspired binary code similarity comparison beyond function pairs. In Network and Disctributed Systems Security (NDSS) Sympsium, San Diego, California, 1–15.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.