DocumentCode :
2709412
Title :
An approach to support Web service classification and annotation
Author :
Bruno, Marcello ; Canfora, Gerardo ; Di Penta, Massimiliano ; Scognamiglio, Rita
Author_Institution :
Dept. of Eng., Univ. of Sannio, Benevento, Italy
fYear :
2005
fDate :
29 March-1 April 2005
Firstpage :
138
Lastpage :
143
Abstract :
The need for supporting the classification and semantic annotation of services constitutes an important challenge for service-centric software engineering. Late-binding and, in general, service matching approaches, require services to be semantically annotated. Such a semantic annotation may require, in turn, to be made in agreement to a specific ontology. Also, a service description needs to properly relate with other similar services. This paper proposes an approach to i) automatically classify services to specific domains and ii) identify key concepts inside service textual documentation, and builds a lattice of relationships between service annotations. Support vector machines and formal concept analysis have been used to perform the two tasks. Results obtained classifying a set of Web services show that the approach can provide useful insights in both service publication and service retrieval phases.
Keywords :
classification; formal specification; ontologies (artificial intelligence); semantic Web; support vector machines; Web service classification; formal concept analysis; information retrieval; ontology; semantic annotation; service-centric software engineering; support vector machine; Concrete; Documentation; Lattices; Ontologies; Quality of service; Software engineering; Support vector machine classification; Support vector machines; US Department of Transportation; Web services; Ontology Building; Semantic Annotation; Service Classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
e-Technology, e-Commerce and e-Service, 2005. EEE '05. Proceedings. The 2005 IEEE International Conference on
Print_ISBN :
0-7695-2274-2
Type :
conf
DOI :
10.1109/EEE.2005.31
Filename :
1402283
Link To Document :
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