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Enriching non-taxonomic relations extracted from domain texts

Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subje...

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Main Authors:	N.F., Nabila,, A., Mamat,, Murad, Azmi, N., Mustapha,
Format:	Conference Paper
Language:	en_US
Published:	2015
Subjects:	Non-taxonomic relation Relation Extraction Relation Identification
Online Access:	http://ddms.usim.edu.my/handle/123456789/9194
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id	my.usim-9194
record_format	dspace
spelling	my.usim-91942015-08-25T04:34:29Z Enriching non-taxonomic relations extracted from domain texts N.F., Nabila, A., Mamat, Murad, Azmi N., Mustapha, Non-taxonomic relation Relation Extraction Relation Identification Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subject and object that occurs in a sentence. However, the number of relations that has been identified does not properly represent the domain as the methods only identify a portion of the total relations from domain texts. In this paper, we present a method that increases the number of relations extracted and thus properly represent the domain. In this method, all potential relations are first generated and then less significant ones, based on their frequency, are removed. The method has been tested on a collection of texts that described electronic voting machine and the result is encouraging. © 2011 IEEE. 2015-08-25T04:34:29Z 2015-08-25T04:34:29Z 2011 Conference Paper 9781-6128-4353-7 http://ddms.usim.edu.my/handle/123456789/9194 en_US
institution	Universiti Sains Islam Malaysia
building	USIM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universit Sains Islam i Malaysia
content_source	USIM Institutional Repository
url_provider	http://ddms.usim.edu.my/
language	en_US
topic	Non-taxonomic relation Relation Extraction Relation Identification
spellingShingle	Non-taxonomic relation Relation Extraction Relation Identification N.F., Nabila, A., Mamat, Murad, Azmi N., Mustapha, Enriching non-taxonomic relations extracted from domain texts
description	Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subject and object that occurs in a sentence. However, the number of relations that has been identified does not properly represent the domain as the methods only identify a portion of the total relations from domain texts. In this paper, we present a method that increases the number of relations extracted and thus properly represent the domain. In this method, all potential relations are first generated and then less significant ones, based on their frequency, are removed. The method has been tested on a collection of texts that described electronic voting machine and the result is encouraging. © 2011 IEEE.
format	Conference Paper
author	N.F., Nabila, A., Mamat, Murad, Azmi N., Mustapha,
author_facet	N.F., Nabila, A., Mamat, Murad, Azmi N., Mustapha,
author_sort	N.F., Nabila,
title	Enriching non-taxonomic relations extracted from domain texts
title_short	Enriching non-taxonomic relations extracted from domain texts
title_full	Enriching non-taxonomic relations extracted from domain texts
title_fullStr	Enriching non-taxonomic relations extracted from domain texts
title_full_unstemmed	Enriching non-taxonomic relations extracted from domain texts
title_sort	enriching non-taxonomic relations extracted from domain texts
publishDate	2015
url	http://ddms.usim.edu.my/handle/123456789/9194
_version_	1645152560250617856
score	13.211869

Enriching non-taxonomic relations extracted from domain texts

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