Hybrid Deep Learning for Sentiment Polarity Determination of Arabic Microblogs
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[1] Mahmoud Al-Ayyoub,et al. A prototype for a standard arabic sentiment analysis corpus , 2016, Int. Arab J. Inf. Technol..
[2] Yoon Kim,et al. Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.
[3] Abdelkamel Tari,et al. Data and Text Mining Techniques for Classifying Arabic Tweet Polarity , 2016 .
[4] Rehab Duwairi,et al. Detecting sentiment embedded in Arabic social media - A lexicon-based approach , 2015, J. Intell. Fuzzy Syst..
[5] Mahmoud Al-Ayyoub,et al. Evaluating SentiStrength for Arabic Sentiment Analysis , 2016, 2016 7th International Conference on Computer Science and Information Technology (CSIT).
[6] Bing Liu,et al. Sentiment Analysis and Opinion Mining , 2012, Synthesis Lectures on Human Language Technologies.
[7] Mahmoud Al-Ayyoub,et al. Arabic sentiment analysis: Lexicon-based and corpus-based , 2013, 2013 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT).
[8] Yelong Shen,et al. Learning semantic representations using convolutional neural networks for web search , 2014, WWW.
[9] Pengfei Duan,et al. Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification , 2016, COLING.
[10] Nazlia Omar,et al. A Comparative Study of Feature Selection and Machine Learning Algorithms for Arabic Sentiment Classification , 2014, AIRS.
[11] Heider A. Wahsheh,et al. Arabic sentiment polarity identification using a hybrid approach , 2015, 2015 6th International Conference on Information and Communication Systems (ICICS).
[12] Verena Rieser,et al. An Arabic Twitter Corpus for Subjectivity and Sentiment Analysis , 2014, LREC.
[13] Phil Blunsom,et al. A Convolutional Neural Network for Modelling Sentences , 2014, ACL.
[14] Lixin Tao,et al. Word embeddings for Arabic sentiment analysis , 2016, 2016 IEEE International Conference on Big Data (Big Data).
[15] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[16] Bashar Al Shboul,et al. Multi-way sentiment classification of Arabic reviews , 2015, 2015 6th International Conference on Information and Communication Systems (ICICS).
[17] Verena Rieser,et al. iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases , 2016, *SEMEVAL.
[18] Sven Behnke,et al. Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition , 2010, ICANN.
[19] Samhaa R. El-Beltagy,et al. Building Large Arabic Multi-domain Resources for Sentiment Analysis , 2015, CICLing.
[20] Hazem M. Hajj,et al. Deep Learning Models for Sentiment Analysis in Arabic , 2015, ANLP@ACL.
[21] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[22] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[23] El-Sayed M. El-Alfy,et al. Using Word Embedding and Ensemble Learning for Highly Imbalanced Data Sentiment Analysis in Short Arabic Text , 2017, ANT/SEIT.
[24] Saif Mohammad,et al. How Translation Alters Sentiment , 2016, J. Artif. Intell. Res..
[25] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[26] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[27] Amir F. Atiya,et al. ASTD: Arabic Sentiment Tweets Dataset , 2015, EMNLP.