Ontologies play a vital role in many web- and internet-related applications. This work presents a system for accelerating the ontology building process via semi-automatically learning a hierarchal ontology given a set of domain-specific web documents and a set of seed concepts. The methods are tested with web documents in the domain of agriculture. The ontology is constructed through the use of two complementary approaches. The presented system has been used to build an ontology in the agricultural domain using a set of Arabic extension documents and evaluated against a modified version of the AGROVOC ontology.
Description
IngentaConnect Ontology learning from domain specific web documents
%0 Journal Article
%1 Hazman:30May2009:1744-2621:24
%A Hazman, Maryam
%A El-Beltagy, Samhaa R.
%A Rafea, Ahmed
%D 2009
%J International Journal of Metadata, Semantics and Ontologies
%K learning ol ontology
%P 24-33(10)
%R doi:10.1504/IJMSO.2009.026251
%T Ontology learning from domain specific web documents
%U http://www.ingentaconnect.com/content/ind/ijmso/2009/00000004/F0020001/art00003
%V 4
%X Ontologies play a vital role in many web- and internet-related applications. This work presents a system for accelerating the ontology building process via semi-automatically learning a hierarchal ontology given a set of domain-specific web documents and a set of seed concepts. The methods are tested with web documents in the domain of agriculture. The ontology is constructed through the use of two complementary approaches. The presented system has been used to build an ontology in the agricultural domain using a set of Arabic extension documents and evaluated against a modified version of the AGROVOC ontology.
@article{Hazman:30May2009:1744-2621:24,
abstract = {Ontologies play a vital role in many web- and internet-related applications. This work presents a system for accelerating the ontology building process via semi-automatically learning a hierarchal ontology given a set of domain-specific web documents and a set of seed concepts. The methods are tested with web documents in the domain of agriculture. The ontology is constructed through the use of two complementary approaches. The presented system has been used to build an ontology in the agricultural domain using a set of Arabic extension documents and evaluated against a modified version of the AGROVOC ontology.},
added-at = {2011-02-09T15:32:47.000+0100},
author = {Hazman, Maryam and El-Beltagy, Samhaa R. and Rafea, Ahmed},
biburl = {https://www.bibsonomy.org/bibtex/2323c8bdedc8a4643232a498ac03d6407/hotho},
description = {IngentaConnect Ontology learning from domain specific web documents},
doi = {doi:10.1504/IJMSO.2009.026251},
interhash = {fe27d687bcba91a7a6fe51eec9a2b87d},
intrahash = {323c8bdedc8a4643232a498ac03d6407},
journal = {International Journal of Metadata, Semantics and Ontologies},
keywords = {learning ol ontology},
pages = {24-33(10)},
timestamp = {2011-02-09T15:32:47.000+0100},
title = {Ontology learning from domain specific web documents},
url = {http://www.ingentaconnect.com/content/ind/ijmso/2009/00000004/F0020001/art00003},
volume = 4,
year = 2009
}