Using long short-term memory deep neural networks for aspect-based sentiment analysis of Arabic reviews

Author:

Al-Smadi MohammadORCID,Talafha Bashar,Al-Ayyoub Mahmoud,Jararweh Yaser

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference84 articles.

1. Abdul-Mageed M, Diab M (2012) Toward building a large-scale Arabic sentiment lexicon. In: Proceedings of the 6th international global WordNet conference, pp 18–22

2. Agerri R, Bermudez J, Rigau G (2014) Ixa pipeline: efficient and ready to use multilingual nlp tools. In: LREC, pp 3823–3828

3. Al-Smadi M, Al-Ayyoub M, Al-Sarhan H, Jararweh Y (2015a) Using aspect-based sentiment analysis to evaluate arabic news affect on readers. In: 2015 IEEE/ACM 8th international conference on utility and cloud computing (UCC), IEEE, pp 436–441

4. Al-Smadi M, Qawasmeh O, Talafha B, Quwaider M (2015b) Human annotated Arabic dataset of book reviews for aspect based sentiment analysis. In: future internet of things and cloud (FiCloud), 2015 3rd international conference, IEEE, pp 726–730

5. Al-Smadi M, Al-Ayyoub M, Al-Sarhan H, Jararweh Y (2016a) An aspect-based sentiment analysis approach to evaluating Arabic news affect on readers. J Univers Comput Sci (JUCS) 22:630–649

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