Topic Segmentation for Textual Document Written in Arabic Language

Abstract

Topic segmentation is important for many natural language processing applications such as information retrieval, text summarization... In our work, we are interested in the topic segmentation of textual document. We present a survey of related works particularly C99 and TextTiling. Then, we propose an adaptation of these topic segmenters for textual document written in Arabic language named as ArabC99 and ArabTextTiling. For experimental results, we construct an Arabic corpus based on newspapers of different Arab countries. Finally, we evaluate the performance of these new segmenters by comparing them together and to related works using the metrics WindowDiff and F-measure.

ArA*summarizer: An Arabic text summarization system based on subtopic segmentation and using an A* algorithm for reduction

“…The authors' system was compared against three algorithms: SeLeCT (Stokes, Carthy, & Smeaton, , LCseg Galley, McKeown, Fosler‐lussier, & Jing, , and TextTiling (Hearst, . The works of Harrag, Hamdi‐Cherif, and Al‐Salman (); Chaibi et al (); Naili, Chaibi, and Ghezala () consist on a comparison between TextTiling and C99 algorithms implemented on Arabic texts. Harrag et al () developped ArabTiling and TopSegArab (which are, respectively, an adaptation of TextTiling and C99 segmenters).…”

“…In order to evaluate the performance of our subtopic segmentation technique, we made a comparison with five other topic segmenters basing on lexical cohesion detection, ModSeleCT El‐Shayeb et al, , ArabTiling and TopSegArab Harrag et al, , and ArabTextTiling and ArabC99 Chaibi et al, . The test corpus is made up of two collections of 100 articles each.…”

“…It aims to find in a text a set of portions thematically coherent and distinct of the neighbouring portions Choi, 2000. In last years, several approaches have been proposed for topic segmentation that can be classified into endogenous or exogenous approaches. The former exploits the information contained in the text to be segmented such as lexical repetition (see Chaibi, Naili, & Sammoud, 2014). The latter uses external resources like: thesaurus, dictionary, and co-occurrence network.…”

“…The two systems are implemented for information retrieval where they confirmed that the use of topic segmentation gives better results than without. Chaibi et al (), on their part, developped ArabC99 and ArabTextTiling (which are, respectively, an adaptation of TextTiling and C99). Their evaluation results show that ArabC99 is better than TextTiling Arbic version.…”

Ecletic Method for Arabic Learning in Islamic School of Indonesia

“…This approach also requires the students to understand situation depicted by learning materials deductively. Reviews delivered by the teachers after giving each material should be solved on each aspect to strengthen their understanding about such material (Alomar, Wanick, & Wills, 2016;Chaibi, Naili, & Sammoud, 2014;Dajani, 2015). At the beginning, on the sidelines, or at the end of each meeting, Arabic teacher, which is simultaneously being motivator for his/her students to understand that Arabic language is important for them now and in the future and learning Arabic language is not difficult when they are paying great attention to it and doing practices seriously and intensively.…”