Hot-Keys Elicitation using Hybrid Text-Mining Classification for Arabic Humanities Articles Criticism

  • Baraa Hasan Hadi, Tareef Kamil Mustafa

Abstract

Humanities is a study interested in human societies and cultures, including obsolete and modernistic languages, law, politics, religion, philosophy, history, literature, and art.  In these fields, several critics may face some difficulties in makingan automated decision, particularly regarding the interests of the audiences through their opinions about novels, poets, movies that are posted online. Within this perspective, the recent growth to texted documents due to the increase in the content of the text data obtainable online and from social networking. Social networks are active sites in which users may manifest their opinions, views, and comments in different fields of interest. Accordingly, it requires some fundamental and specific processes to wrap up this increase. Due to the structural and linguistic intricacy of texts in Arabic, it is necessary to implement such methods, especially in identifying these texts in the Arabic language. The purpose of this study is to consider using the Stylometric technique to parse the document as parallel to the traditional procedures that have been used by researchers such as the syntactic and lexical techniques.

The Stylometric technique is a language-independent task, which is considered a substantial factor in this research that could assist to artistic critics in their choices. Subsequently, the outcome could make the critic's decision easier and summarized in a hot-keys structure. The data used in thismannerwerethecomments representing the opinions, views of the audience. The comments were chunked, filtered,and organized in the form of a set of attributes. These attributes help extract a brief text from the official online web page of 'Cinemana' data,which are posted on Earth-link share Cloud. This web page contains the most significant movie database in the Middle East, which offers a wide range of options, including adventures, comedies, dramas, family, crime, romance, and more. Additionally, Supervised Machine-Learning techniques have been implemented by involving some selected data-mining algorithms.

Published
2020-06-01
How to Cite
Baraa Hasan Hadi, Tareef Kamil Mustafa. (2020). Hot-Keys Elicitation using Hybrid Text-Mining Classification for Arabic Humanities Articles Criticism. International Journal of Advanced Science and Technology, 29(10s), 3068-3077. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/20696
Section
Articles