Arafat Awajan
Text and Document Classification Technologies Topic Modeling Natural Language Processing Techniques Advanced Text Analysis Techniques Sentiment Analysis and Opinion Mining Text Readability and Simplification Artificial Intelligence

Educational Journey

Université de Franche-Comté

Ph.D.

Experience

Royal Scientific Society

Vice President for Scientific Research

2024 - Present

Princess Sumaya University for Technology

Vice President

1993 - Present • University Presidency

Mutah University

President

2020 - 2023 • University Presidency
Show all 9 experience

Editors Role

Reviewer

GJCST

0 -

Research

Hybrid Technique for Arabic Text Compression

Article February 21, 2015

Arabic content on the Internet and other digital media is increasing exponentially, and the number of Arab users of these media has multiplied by more than 20 over the past five years. There is a real need to save allocated space for this content as well as allowing more efficient usage, searching, and retrieving information operations on this content. Using techniques borrowed from other languages or general data compression techniques, ignoring the proper features of Arabic has limited success in terms of compression ratio. In this paper, we present a hybrid technique that uses the linguistic features of Arabic language to improve the compression ratio of Arabic texts. This technique works in phases. In the first phase, the text file is split into four different files using a multilayer model-based approach. In the second phase, each one of these four files is compressed using the Burrows-Wheeler compression algorithm.