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Title:	Rule-based approach for Arabic grammatical relation extraction
Authors:	Othman Ibrahim Hammadi (P53699)
Supervisor:	Mohd. Juzaidin Ab Aziz, Prof. Dr.
Keywords:	Arabic language -- Grammar Generative Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia
Issue Date:	19-Jan-2012
Description:	Grammatical Relation (GR) can be defined as a linguistic relation established by grammar, where the linguistic relation is an association between linguistic forms or constituents. Fundamentally, GRs determine grammatical behaviour, such as the placement of a word in a clause, verb agreement and passivity behaviour. The GR of Arabic is a necessary prerequisite for many natural language processing applications, such as machine translation and information retrieval. This study focuses on GR related problems of Arabic, and addresses these issues with an optimum solution. The main goal of this study is to develop an efficient GR extraction technique to analyse modern standard Arabic sentences. This research will propose a Rule-Based production method, to recognize shallow parsing (Chunking); as a Rule-Based approach has been successfully used in developing many other natural language processing systems. In order to eradicate the problems of sentence structure recognition, the proposed technique will enhance the basic representations of Arabic, such as: Noun Phrase (NP), Verb Phrase (VP), Preposition Phrase (PP), and Adjective Phrase (AP). We have implemented and evaluated a Rule-Based approach that handles chunking and GRs of Arabic sentences. The system was manually tested on 80 Arabic sentences, with the length of each sentence ranging from 3 to 20 words. The results obtained achieved an F-score of 89.60 % precision, which is significantly better than other state-of-the-art Arabic GR results published. This result proves the viability of this approach for the GR extraction of Arabic sentences.,Certification of Master's/Doctoral Thesis" is not available
Pages:	97
Call Number:	QA76.9.D343H344 2012 3 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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