Sentiment Analysis of Arabic Sequential Data Using Traditional and Deep Learning: A Review
暂无分享,去创建一个
[1] Matthew England,et al. Improving Sentiment Analysis in Arabic Using Word Representation , 2018, 2018 IEEE 2nd International Workshop on Arabic and Derived Script Analysis and Recognition (ASAR).
[2] Imane Guellil,et al. Arabic sentiment analysis: studies, resources, and tools , 2019, Social Network Analysis and Mining.
[3] Ammar Mohammed,et al. Deep learning approaches for Arabic sentiment analysis , 2019, Social Network Analysis and Mining.
[4] Babar Hayat,et al. Sentiment Analysis Using Deep Learning Techniques: A Review , 2017, International Journal of Advanced Computer Science and Applications.
[5] Banu Diri,et al. Abstract feature extraction for text classification , 2012, Turkish Journal of Electrical Engineering and Computer Sciences.
[6] Santanu Kumar Rath,et al. Classification of sentiment reviews using n-gram machine learning approach , 2016, Expert Syst. Appl..
[7] Azzeddine Mazroui,et al. Studying the effect of characteristic vector alteration on Arabic sentiment classification , 2019 .
[8] Mahmoud Al-Ayyoub,et al. Are emoticons good enough to train emotion classifiers of Arabic tweets? , 2016, 2016 7th International Conference on Computer Science and Information Technology (CSIT).
[9] Vivek Kumar,et al. Implementation of n-gram Methodology for Rotten Tomatoes Review Dataset Sentiment Analysis , 2017, Int. J. Knowl. Discov. Bioinform..
[10] Ayah Soufan,et al. Deep Learning for Sentiment Analysis of Arabic Text , 2019, ArabWIC 2019.
[11] Maria Virvou,et al. The effect of preprocessing techniques on Twitter sentiment analysis , 2016, 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA).
[12] Ahmed Alsayat,et al. A comprehensive study for Arabic Sentiment Analysis (Challenges and Applications) , 2020 .
[13] Xiaoyong Du,et al. Neural Bag-of-Ngrams , 2017, AAAI.
[14] Aida Mustapha,et al. Comparative Analysis for Arabic Sentiment Classification , 2019, ACRIT.
[15] Ahmed Z. Emam,et al. Sentiment Analysis of Saudi Dialect Using Deep Learning Techniques , 2019, 2019 International Conference on Electronics, Information, and Communication (ICEIC).
[16] Arjun Srinivas Nayak,et al. Survey on Pre-Processing Techniques for Text Mining , 2016 .
[17] Mohamed Touahria,et al. Improving sentiment analysis in Arabic: A combined approach , 2019, J. King Saud Univ. Comput. Inf. Sci..
[18] Susan Athey,et al. The Impact of Machine Learning on Economics , 2018, The Economics of Artificial Intelligence.
[19] Raddouane Chiheb,et al. Sentiment analysis in Arabic: A review of the literature , 2017, Ain Shams Engineering Journal.
[20] Nizar Habash,et al. A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models , 2017, WANLP@EACL.
[21] Shuai Wang,et al. Deep learning for sentiment analysis: A survey , 2018, WIREs Data Mining Knowl. Discov..
[22] Mihaela Cocea,et al. Learning Sentiment from Students' Feedback for Real-Time Interventions in Classrooms , 2014, ICAIS.
[23] Masoumeh Zareapoor,et al. Feature Extraction or Feature Selection for Text Classification: A Case Study on Phishing Email Detection , 2015 .
[24] Norjihan Abdul Ghani,et al. Social media big data analytics: A survey , 2019, Comput. Hum. Behav..
[25] A. Elnagar,et al. Hotel Arabic-Reviews Dataset Construction for Sentiment Analysis Applications , 2018 .
[26] Quratulain Rajput,et al. Lexicon-Based Sentiment Analysis of Teachers' Evaluation , 2016, Appl. Comput. Intell. Soft Comput..
[27] M. A. Jawale,et al. Fundamentals of Sentiment Analysis: Concepts and Methodology , 2016, Sentiment Analysis and Ontology Engineering.
[28] Mohammed Al-Kabi,et al. Evaluating social context in arabic opinion mining , 2018, Int. Arab J. Inf. Technol..
[29] Hazem M. Hajj,et al. Deep Learning Models for Sentiment Analysis in Arabic , 2015, ANLP@ACL.
[30] Marco Vannucci,et al. Variable Selection and Feature Extraction Through Artificial Intelligence Techniques , 2013 .
[31] Erkki Sutinen,et al. Exploiting sentiment analysis to track emotions in students' learning diaries , 2013, Koli Calling '13.
[32] Anjali Ganesh Jivani,et al. A Comparative Study of Stemming Algorithms , 2011 .
[33] Hazem M. Hajj,et al. AROMA: A Recursive Deep Learning Model for Opinion Mining in Arabic as a Low Resource Language , 2017, ACM Trans. Asian Low Resour. Lang. Inf. Process..
[34] Patrizia Grifoni,et al. Approaches, Tools and Applications for Sentiment Analysis Implementation , 2015 .