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Title:	Rule based shallow parser for Arabic language
Authors:	Mona Ali Mohammed (P47953)
Supervisor:	Nazlia Omar, Dr.
Keywords:	Arabic language Computational linguistics
Issue Date:	2011
Description:	Shallow syntactic parsing (also called partial parsing or chunking) is an approach to language processing that computes a basic analysis of sentence structure rather than attempting full syntactic analysis. It is an analysis of a sentence which identifies the constituents (noun groups, verb groups, prepositional groups, etc), but does not specify their internal structure, nor their role in the main sentence .The shallow parser is an important preprocessing tool, which is used in many natural language processing such as Named Entity Recognition, Information Retrieval, Question Answering and etc. In this thesis we present a novel rule based method for Arabic shallow parser, This work is based on a critical analysis of the Arabic sentences architecture. It discusses various idiosyncrasies of Arabic sentences to derive more accurate rules to detect the start and the end boundaries of each clause in an Arabic sentence. New rules are proposed to the shallow parser features up to the generation of two levels from full parse-tree. Part of speech (POS) tags are input to the system that will identify the noun phrases (NPs), verb phrases (VPs), and prepositional phrases (PPs) constituents. We describe an implementation and evaluate the rule-based shallow parser that handles chunking of Arabic sentences. The system was tested manually on 70 Arabic sentences which composed of 1776 words, with the length of the sentences between 4 to 50 words. The result obtained is significantly better than state of the art Arabic published results, which achieved an F-scores of 97 %. This result prove the viability of this approach for Arabic sentences shallow parser.,Master/Sarjana
Pages:	116
Call Number:	QA76.9.N38M84 2011 3 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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