Arguments extraction for e-health services based on text mining tools
Dena Kadhim Muhsen, Sura Mazin Ali, Rana Mohammed Hassan Zaki, Amjed Abbas Ahmed · Periodicals of Engineering and Natural Sciences (PEN) · 2021
The task of recognizing arguments and their components in text is known as argument extraction. Most arguments might be broken down into a petition and at least one premise that support it. A method to extract arguments is suggested in this work. The major words which are of high importance in arguments extraction were included in the suggested method on the basis of Arabic lexicon. The lexicon tool was used to apply classic text mining stages. The dataset, which includes over 3000 petitions, was collected from the Citizen Affairs Department in the Ministry of Health-Iraq. In addition, the experimental results exhibit that the suggested method extracts arguments from collected dataset with a 93.5% accuracy ratio.