Discovering plain-text-described services based on ontology learning

Dong, H; Hussain, FK; Bouguettaya, A

Discovering plain-text-described services based on ontology learning

Dong, H Hussain, FK

Bouguettaya, A

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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), 2014, 8836 pp. 673 - 681
Issue Date:: 2014-01-01

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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	Bouguettaya, A	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8836 pp. 673 - 681	en_US
dc.identifier.isbn	9783319126425	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121723
dc.description.abstract	© Springer International Publishing Switzerland 2014. In this paper, we present an approach to efficiently discover domain-specific services that are described by plain text over the Internet. Plain-text-described service advertisements account for the vast majority of service advertisements over the Internet, but current research rarely focuses on this area. To address this issue, we design a domain-ontology-based approach for automatic plain-text-described service discovery. This approach incorporates a plain-text-described service ontology for standard service description, a plaintext- described service discovery framework for domain-relevant service discovery and ontology learning, and a machine-learning-based model for ontologybased service functionality annotation. The experimental results show that this approach is able to efficiently discover more relevant plain-text-described services than other approaches.	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	Discovering plain-text-described services based on ontology learning	en_US
dc.type	Conference Proceeding
utslib.citation.volume	8836	en_US
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	080109 Pattern Recognition and Data Mining	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.publication-status	Published	en_US
pubs.volume	8836	en_US

Abstract:

© Springer International Publishing Switzerland 2014. In this paper, we present an approach to efficiently discover domain-specific services that are described by plain text over the Internet. Plain-text-described service advertisements account for the vast majority of service advertisements over the Internet, but current research rarely focuses on this area. To address this issue, we design a domain-ontology-based approach for automatic plain-text-described service discovery. This approach incorporates a plain-text-described service ontology for standard service description, a plaintext- described service discovery framework for domain-relevant service discovery and ontology learning, and a machine-learning-based model for ontologybased service functionality annotation. The experimental results show that this approach is able to efficiently discover more relevant plain-text-described services than other approaches.

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http://hdl.handle.net/10453/121723