Arabic Opinion Mining System for E-Services Based On Ontology and Machine Learning

Abstract

Maha Mansour, Randa Elwakil ,Hoda Wageih and Magdy Aboul-Ela

With the growing use of E-Services in the Arab world, there is a need for efficient methods to analyze customer feedback and opinions. This research is proposing an Arabic opinion mining system for E-Services based on ontology and machine learning techniques. The system utilizes an Arabic ontology to capture domain-specific vocabulary and relationships between features and a machine learning model to classify customer feedback into positive, negative, or neutral sentiments. By evaluating the performance of the system using several domains datasets for Arabic customer reviews of various e-services, and the results show that the system achieves a high accuracy level. Comparing the performance of the proposed system to traditional polarity and subjectivity approaches.

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