LSI Authentication-Based Arabic to English Text Converter

Abstract

Due to the large amount of Arabic text produced on a daily basis, there is a need to analyze these texts. Following a comprehensive literature review, there become clear several issuesrelated to Arabic text summaries, keyword extraction, and sentiment analyses. These issuesoccur owing to several factors, such as the structure and morphology of Arabic text, a lack ofmachine-readable Arabic dictionaries, insufficient tools to manage Arabic text, no standarddatasets, inherently cursive scripts, and isolated characters; thus, there is a need to createArabic text in forms that can be easily read by machine learning, deep learning algorithms, andexisting analysis tools. To achieve this, the Arabic texts must be converted into English texts.This paper proposes a lexicon called the AEC-Lexicon for use by all researchers workingin Arabic, which is based on the Arabic case system and converts Arabic text into Englishtext. Based on the experimental results of latent semantic indexing (LSI), it was found thattexts generated from the proposed work exhibited a significant improvement over existingwork (converted Arabic to English texts), considering reading and understanding as well asthe relevance to the original Arabic text