What is it about?
Due to the obvious significant expansion in the number of online Arabic textual information, Arabic Text Summarization has become a focus of intense research. Manual text summarization necessitates a large investment of time, effort, and money. Hence, Automatic Arabic Text Summarization (AATS) is currently necessary to create accurate and relevant summaries from the huge amount of accessible content. The developed techniques and methodologies for AATS are still in their immaturity because of the intrinsic complexity of the structure and morphology of the Arabic language.
Why is it important?
This paper addresses the fundamental issues for Arabic text summarization and analyzes the available approaches and systems. AATS methods could be categorized as extractive, abstractive, hybrid extractive to abstractive. The extractive method selects and combines the most important sentences from the input document(s) to produce the summary. While the abstractive method needs deep understanding of the input document(s) for creating the summary with sentences that differ from the original ones. The extractive to abstractive method is a hybrid strategy for creating an informative and cohesive summary using the extractive summary as a first step. A comparison is implemented between seven selected recent approaches with a unified dataset and the results are discussed.