Computational Analysis of Printed Arabic Text Database for Natural Language Processing

Abstract

A frequency dictionary of printed Arabic text is essential for natural language processing. It includes 1,251 XML files of Arabic documents collected from ten newspapers and magazines from different countries and created as the PATD database. A total of 2,344 articles were created with various structures: open vocabulary, multi-font, multi-size, and multi-style text. From these articles, 1,102,078 tokens, 19,926 sentences, and 1,000,000 words were extracted. This dictionary provides detailed information for each word, including English equivalents, usage statistics, usage distribution, and the most widely used terms. A thematic vocabulary list of the top words on various topics is also provided. This frequency dictionary is a useful resource of modern Arabic vocabulary for various specialists, students, and learners. The frequency dictionary is freely available to interested researchers on the webpage.

Keywords

• Arabic language
• vocabulary
• Arabic documents
• frequency dictionary
• Arabic printed text database