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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15183

Title: Semantic-Based Segmentation of Arabic Texts
Authors: Hassan Mathkour
W. Al-Sanea
A. Touir
Keywords: Text segmentation, Arabic text processing, computational linguistic, information retrieval
Issue Date: 2008
Publisher: Information Technology Journal
Abstract: In this study, we present an automatic technique to help segment the Arabic texts while preserving the semantics. The technique is based on empirical study on the sentences and clauses connectos. It has evolved from tedious analysis of various Arabic texts and from observation that have been noted over a long period of time. The analysis made it possible to realize the functionality of each connector in terms of separating standlone segments in the Arabic texts. This has lead to categorization of active and passive connectors to develop an algorithm that respects the semantic of the text to identify the segments of given Arabic texts. The algorithm has been implemented and experimented with Various Arabic essays were segmented using the algorithm and the results were compared to that of manual segmentations performed by linguistic experts.
URI: http://hdl.handle.net/123456789/15183
Appears in Collections:College of Computer and Information Sciences

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