Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach

This thesis present two new techniques namely Unambiguous Entity Extraction (UEE) and Unambiguous Fact Extraction (UFE) to resolve ambiguiti in entity and fact extraction. Both techniques are obtained by hybriding 4 major theories and approaches namely, possibility theory, fuzzy sets, a knowledge-ba...

Full description

Saved in:

Bibliographic Details
Main Author:	Al Fawareh, Hejab Ma'azer Khaled
Format:	Thesis
Language:	eng eng
Published:	2010
Subjects:	QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/2401/1/Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf https://etd.uum.edu.my/2401/2/1.Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uum-etd.2401
record_format	uketd_dc
spelling	my-uum-etd.24012013-07-24T12:15:51Z Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach 2010-07 Al Fawareh, Hejab Ma'azer Khaled Sheik Osman, Wan Rozaini Mohd Norwawi, Norita College of Arts and Sciences (CAS) College of Arts and Sciences QA71-90 Instruments and machines This thesis present two new techniques namely Unambiguous Entity Extraction (UEE) and Unambiguous Fact Extraction (UFE) to resolve ambiguiti in entity and fact extraction. Both techniques are obtained by hybriding 4 major theories and approaches namely, possibility theory, fuzzy sets, a knowledge-based approach, NLP techniques (syntactic and semantic processing). In this thesis, a word that is classified into to Noun part-of-speech is considered as an entity. An entity is ambiguous if it has more than one semantic. The UEE technique is designed and developed to assign the most possible semantic to the word. The technique was tested using 12 test cases with 111 sentences. The obtained results indicate that UEE technique is able to give precision rate of 85.7% and recall rate of 80.3%. On the other hands, UFE focuses on extracting an ambiguous fact from a sentence. A fact is a meaning that can be formally represented as a statement and determined its truthfulness. A sentence contains an ambiguous fact if it can be interpreted into more than one meaning. The UFE technique is designed and developed to select the most possible fact by selecting the most possible meaning from a sentence. In evaluating UFE technique, test cases have been created and tested. Each test case consist of sentences in the range of 5 to 8. The obtained results in the form of predicate calculus are evaluated manually. The results suggest that UFE technique is successful. 2010-07 Thesis https://etd.uum.edu.my/2401/ https://etd.uum.edu.my/2401/1/Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf application/pdf eng validuser https://etd.uum.edu.my/2401/2/1.Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf application/pdf eng public http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000761704 Ph.D. doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Sheik Osman, Wan Rozaini Mohd Norwawi, Norita
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Al Fawareh, Hejab Ma'azer Khaled Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
description	This thesis present two new techniques namely Unambiguous Entity Extraction (UEE) and Unambiguous Fact Extraction (UFE) to resolve ambiguiti in entity and fact extraction. Both techniques are obtained by hybriding 4 major theories and approaches namely, possibility theory, fuzzy sets, a knowledge-based approach, NLP techniques (syntactic and semantic processing). In this thesis, a word that is classified into to Noun part-of-speech is considered as an entity. An entity is ambiguous if it has more than one semantic. The UEE technique is designed and developed to assign the most possible semantic to the word. The technique was tested using 12 test cases with 111 sentences. The obtained results indicate that UEE technique is able to give precision rate of 85.7% and recall rate of 80.3%. On the other hands, UFE focuses on extracting an ambiguous fact from a sentence. A fact is a meaning that can be formally represented as a statement and determined its truthfulness. A sentence contains an ambiguous fact if it can be interpreted into more than one meaning. The UFE technique is designed and developed to select the most possible fact by selecting the most possible meaning from a sentence. In evaluating UFE technique, test cases have been created and tested. Each test case consist of sentences in the range of 5 to 8. The obtained results in the form of predicate calculus are evaluated manually. The results suggest that UFE technique is successful.
format	Thesis
qualification_name	Ph.D.
qualification_level	Doctorate
author	Al Fawareh, Hejab Ma'azer Khaled
author_facet	Al Fawareh, Hejab Ma'azer Khaled
author_sort	Al Fawareh, Hejab Ma'azer Khaled
title	Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
title_short	Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
title_full	Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
title_fullStr	Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
title_full_unstemmed	Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach
title_sort	resolving ambiguity in entity and fact extraction through a hybrid approach
granting_institution	Universiti Utara Malaysia
granting_department	College of Arts and Sciences (CAS)
publishDate	2010
url	https://etd.uum.edu.my/2401/1/Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf https://etd.uum.edu.my/2401/2/1.Hejab_Ma%27azer_Khaled_Al_Fawareh.pdf
_version_	1747827336456175616

Resolving Ambiguity in Entity and Fact Extraction Through a Hybrid Approach

Similar Items