Single arabic document summarization using natural language processing technique

This paper presents a method based on natural language processing (NLP) for single Arabic document summarization. The suggested method based on the extractive method to select the most valuable information in the document. However, working with Arabic text is considered as a challenging task, this chapter tries to produce an accurate result by using some of NLP techniques. The proposed method is formed from three phases, the first one work as a pre-processing phase to unify synonyms terms, stemming, remove punctuation marks and remove text decoration. Consequently, it produces the features vectors and scores these features to start to select the clauses with the highest scores then marks it as important clauses. The suggested method’s results are compared versus the traditional methods. In this context, two human experts summarized all the datasets manually in order to prepare a strong compare …