Design of Syntactical Morphological and Semantical Analyzer (SMSA) for Processing Arabic Texts

  • Samar Mouti
  • Fadel Sukkar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3975)


This research describes an ongoing expert system developed for Natural Language Processing (NLP), and presents an approach for Arabic language manipulation, which integrates Syntactical Morphological and Semantical Analyzer (SMSA). Informational goal of SMSA is processing Arabic language from its inductive database, which is organized without dictionary.

Search engine isbuilt up as a high performance linguistic engine that facilitates analyses of written texts in Arabic language, performs full linguistic processing on text, and generates robust parser for Arabic sentences. Learned knowledge is represented in form of rules and facts. Reasoning and inference are accredited to aid grammar induction containing syntactical, morphological and semantical rules, which are conducive towards language processing.

Arabic sentences are divided into two main parts: statement sentence and composition sentence. In turn, statement sentence is divided into a noun, verbal, and conditional sentences. Composition sentence is splited up into imperative and expletive composition. Words are divided into two parts: possession and functional words, also verbs and nouns are sorted in semantical groups.


Semantical Group Arabic Language Semantical Rule Inductive Learning Statement Sentence 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Samar Mouti
    • 1
  • Fadel Sukkar
    • 2
  1. 1.Faculty of Informatics EngineeringUniversity of AleppoAleppoSyria
  2. 2.Cognitive and Neural Systems DepartmentUniversity of BostonBostonUSA

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