A semantic crawler based on an extended CBR algorithm

Dong, H; Hussain, FK; Chang, E

A semantic crawler based on an extended CBR algorithm

Dong, H Hussain, FK

Chang, E

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, 5333 pp. 1076 - 1085
Issue Date:: 2008-01-01

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Field	Value	Language
dc.contributor.author	Dong, H	en_US
dc.contributor.author	Hussain, FK https://orcid.org/0000-0003-1513-8072	en_US
dc.contributor.author	Chang, E	en_US
dc.date.issued	2008-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, 5333 pp. 1076 - 1085	en_US
dc.identifier.isbn	9783540888741	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32944
dc.description.abstract	© Springer-Verlag Berlin Heidelberg 2008. A semantic (web) crawler refers to a series of web crawlers designed for harvesting semantic web content. This paper presents the framework of a semantic crawler that can abstract metadata from online webpages and cluster the metadata by associating them with ontological concepts. The clustering is based on a CBR algorithm which is adopted in the field of problem solving. We reveal the technical details with regard to ontological concept and metadata format, and the extended CBR algorithm. In addition, the system implementation and evaluation details are provided in detail, finalized by our conclusion and further works.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A semantic crawler based on an extended CBR algorithm	en_US
dc.type	Conference Proceeding
utslib.citation.volume	5333	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Monterrey, MEXICO
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	5333	en_US

Abstract:

© Springer-Verlag Berlin Heidelberg 2008. A semantic (web) crawler refers to a series of web crawlers designed for harvesting semantic web content. This paper presents the framework of a semantic crawler that can abstract metadata from online webpages and cluster the metadata by associating them with ontological concepts. The clustering is based on a CBR algorithm which is adopted in the field of problem solving. We reveal the technical details with regard to ontological concept and metadata format, and the extended CBR algorithm. In addition, the system implementation and evaluation details are provided in detail, finalized by our conclusion and further works.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/32944