Abstract: with the increase of opinionated reviews on the web, automatically analyzing and extracting knowledge from those reviews is very important. However, it is a challenging task to be done manually. Opinion mining is a text mining discipline that automatically performs such a task. Most researches done in this field were focused on English texts with very limited researches on Arabic language. This scarcity is because there are a lot of obstacles in Arabic. The aim of this paper is to develop a novel semantic feature-based opinion mining framework for Arabic reviews. This framework utilizes the semantic of ontologies and lexicons in the identification of opinion features and their polarity. Experiments showed that the proposed framework achieved a good level of performance compared with manually collected test data.

Abdullah M. Alkadri and Abeer M. ElKorany. “Semantic Feature Based Arabic Opinion Mining Using Ontology”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.5 (2016). http://dx.doi.org/10.14569/IJACSA.2016.070576

@article{Alkadri2016,
title = {Semantic Feature Based Arabic Opinion Mining Using Ontology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070576},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070576},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Abdullah M. Alkadri and Abeer M. ElKorany}
}