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Published Articles >> Table of Contents >> Abstract
2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06)
pp. 649-652
Web Service Discovery via Semantic Association Ranking and Hyperclique Pattern Discovery
Aabhas V. Paliwal, Rutgers Univ., CIMIC
Nabil R. Adam, Rutgers Univ., CIMIC
Hui Xiong, Rutgers Univ., CIMIC
Christof Bornhovd, SAP Labs, LLC
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI.2006.194
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| Abstract |
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Semantic Web technology is a promising first step for
automated web service discovery. Most current
approaches for web service discovery cater to semantic
web services, i.e., web services that have associated
semantic descriptions. It is unrealistic, however, to expect
all new services to have associated semantic descriptions.
Furthermore, the descriptions of the vast majority of
already existing services do not have explicitly associated
semantics. In this paper we present a novel approach for
web service discovery that combines semantic and
statistical association metrics. Semantic metrics are
based on the semantic aspects of relevant ontology.
Statistical association metrics are based on the
association aspects of web services instances (their inputs
and outputs). Specifically, our approach exploits
semantic relationship ranking for establishing semantic
relevance, and a hyperclique pattern discovery method
for grouping web service parameters into meaningful
associations. These associations combined by the
semantic relevance are then leveraged to discover and
rank web services.
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 Additional Information
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Citation:
Aabhas V. Paliwal, Nabil R. Adam, Hui Xiong, Christof Bornhovd,
"Web Service Discovery via Semantic Association Ranking and Hyperclique Pattern Discovery,"
wi,
pp. 649-652,
2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06),
2006
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