# A Hybrid CNN-LSTM Model for SMS Spam Detection in Arabic and English Messages
## 3 The Proposed Model
### Machine Learning Modeling
#### 3.3.2 Deep Learning
297-313. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON] Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model. _IEEE Trans. Cybern._**2016**, _46_, 2825-2836. [CrossRef] [PubMed]
* [PERSON] and [PERSON] (2016) [PERSON]; [PERSON] [PERSON] An Improved Arabic Handwritten Recognition System Using Deep Support Vector Machines. _Int. J. Multimed. Data Eng. Manag._**2016**, \(7\), 1-20. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Contribution of recurrent connectionist language models in improving LSTM-based Arabic text recognition in videos. _Pattern Recognit._**2017**, _64_, 245-254. [CrossRef]
* [PERSON] et al. (2013) [PERSON]; [PERSON]; [PERSON]; [PERSON] Morpheme-based feature-rich language models using Deep Neural Networks for LVCSR of Egyptian Arabic. In Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, BC, Canada, 26-31 May 2013; pp. 8435-8439. * [PERSON] et al. (2009) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A Deep Learning Approach to Machine Transliteration. In Proceedings of the Fourth Workshop on Statistical Machine Translation, Athens, Greece, 30-31 March 2009; StatMT '09; Association for Computational Linguistics: Stroudsburg, PA, USA, 2009; pp. 233-241. * [PERSON] et al. (2016) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON] Machine Translation Evaluation for Arabic using Morphologically-enriched Embeddings. In Proceedings of the COLING 2016, the 26 th International Conference on Computational Linguistics: Technical Papers, Osaka, Japan, 11-16 December 2016; The COLING 2016 Organizing Committee: Osaka, Japan, 2016; pp. 1398-1408. * [PERSON] (2016) [PERSON] _A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization_; In Proceedings of the ACL 2016 Student Research Workshop, Berlin, Germany, 7-12 August 2016. * [PERSON] et al. (2016) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification. In Proceedings of the COLING 2016, the 26 th International Conference on Computational Linguistics: Technical Papers, Osaka, Japan, 11-16 December 2016; The COLING 2016 Organizing Committee: Osaka, Japan, 2016; pp. 2418-2427. * [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] AROMA: A Recursive Deep Learning Model for Opinion Mining in Arabic as a Low Resource Language. _ACM Trans. Asian Low-Resour. Lang. Inf. Process._**2017**, _16_, 1-20. [CrossRef]
* [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Deep Recurrent neural network vs. support vector machine for aspect-based sentiment analysis of Arabic hotels' reviews. _J. Comput. Sci._**2018**, _27_, 386-393. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]. A C-LSTM Neural Network for Text Classification. _arXiv_**2015**, arXiv:cs.CL/1511.08630. * [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON] S-Detector: an enhanced security model for detecting Smishing attack for mobile computing. _Telecommun. Syst._**2017**, _66_, 29-38. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON] Enhancing spam detection on mobile phone Short Message Service (SMS) performance using FP-growth and Naive Bayes Classifier. In Proceedings of the 2016 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob), Bandung, Indonesia, 13-15 September 2016; pp. 80-84. * [PERSON] and [PERSON] (2018) [PERSON]; [PERSON] [PERSON] SmiDCA: An Anti-Smishing Model with Machine Learning Approach. _Comput. J._**2018**, _61_, 1143-1157. [CrossRef]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] Feature Based Approach for Detection of Smishing Messages in the Mobile Environment. _J. Inf. Technol. Res._**2019**, _12_, 17-35. [CrossRef]
* [PERSON] and [PERSON] (2018) [PERSON]; [PERSON] Rule-Based Framework for Detection of Smishing Messages in Mobile Environment. _Procedia Comput.