Focused crawling for automatic service discovery, annotation, and classification in industrial Digital Ecosystems

Dong, H; Hussain, FK

Focused crawling for automatic service discovery, annotation, and classification in industrial Digital Ecosystems

Dong, H Hussain, FK

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Industrial Electronics, 2011, 58 (6), pp. 2106 - 2116
Issue Date:: 2011-06-01

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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.date.issued	2011-06-01	en_US
dc.identifier.citation	IEEE Transactions on Industrial Electronics, 2011, 58 (6), pp. 2106 - 2116	en_US
dc.identifier.issn	0278-0046	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18238
dc.description.abstract	Digital Ecosystems make use of Service Factories for service entities' publishing, classification, and management. However, before the emergence of Digital Ecosystems, there existed ubiquitous and heterogeneous service information in the Business Ecosystems environment. Therefore, dealing with the preexisting service information becomes a crucial issue in Digital Ecosystems. This issue has not been addressed previously in the literature. In order to resolve this issue, in this paper, we present a conceptual framework for a semantic focused crawler, with the purpose of automatically discovering, annotating, and classifying the service information with the Semantic Web technologies. The technical and evaluation details of the framework are also presented and discussed in this paper. © 2010 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Industrial Electronics	en_US
dc.relation.isbasedon	10.1109/TIE.2010.2050754	en_US
dc.subject.classification	Electrical & Electronic Engineering	en_US
dc.title	Focused crawling for automatic service discovery, annotation, and classification in industrial Digital Ecosystems	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	58	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
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.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	58	en_US

Abstract:

Digital Ecosystems make use of Service Factories for service entities' publishing, classification, and management. However, before the emergence of Digital Ecosystems, there existed ubiquitous and heterogeneous service information in the Business Ecosystems environment. Therefore, dealing with the preexisting service information becomes a crucial issue in Digital Ecosystems. This issue has not been addressed previously in the literature. In order to resolve this issue, in this paper, we present a conceptual framework for a semantic focused crawler, with the purpose of automatically discovering, annotating, and classifying the service information with the Semantic Web technologies. The technical and evaluation details of the framework are also presented and discussed in this paper. © 2010 IEEE.

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http://hdl.handle.net/10453/18238