NDLI: Improve Semantic Web Services Discovery through Similarity Search in Metric Space

Content Provider	IEEE Xplore Digital Library
Author	Minghui Wu Fanwei Zhu Jia Lv Tao Jiang Jing Ying
Copyright Year	2009
Abstract	Most current semantic web services (SWS) discovery approaches focus on the matchmaking of services in a specific description language while in practical application the advertised services are often heterogeneous and distributed. This paper proposes a metric space approach to resolve this problem in which all heterogeneous web services are modeled as metric objects regardless of concrete description languages, and thereby the discovery problem can be treated as similarity search in metric space with a uniform criterion. In the matchmaking process, both the functional semantics and non-functional semantics of the web services are integrated as selection conditions for similarity query. And two types of similarity queries: range query and an improved nearest neighbor query are combined to produce a sorted result set.
Starting Page	297
Ending Page	298
File Size	258132
Page Count	2
File Format	PDF
ISBN	9780769537573
DOI	10.1109/TASE.2009.50
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	similarity search Extraterrestrial measurements Educational institutions Application software Microstrip range query Nearest neighbor searches pkNN Semantic Web Computer science metric space Web services semantic web service Concrete Software engineering
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Improve Semantic Web Services Discovery through Similarity Search in Metric Space

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