Static and dynamic adaptations for service-based systems
Information and Software Technology
Place semantics into context: service community discovery from the WSDL corpus
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
WTCluster: utilizing tags for web services clustering
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
An ontology-based mechanism for automatic categorization of web services
Concurrency and Computation: Practice & Experience
Constrained co-clustering with non-negative matrix factorisation
International Journal of Business Intelligence and Data Mining
Integrating heterogeneous web services from an end user perspective
Proceedings of the 9th Middleware Doctoral Symposium of the 13th ACM/IFIP/USENIX International Middleware Conference
Sparse functional representation for large-scale service clustering
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
A survey of fuzzy service matching approaches in the context of on-the-fly computing
Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
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Web service has already been an important paradigm for web applications. Growing number of services need efficiently locating the desired web services. The similarity metric of web services plays important role in service search and classification. The very small text fragments in WSDL of web services are unsuitable for applying the traditional IR techniques. We describe our approach which supports the similarity search and classification of service operations. The approach firstly employs the external knowledge to compute the semantic distance of terms from two compared services. The similarity of services is measured upon these distances. Previous researches treat terms within the same WSDL documents as the isolated words and neglect the semantic association among them, hence lower down the accuracy of the similarity metric. We provide our method which tries to reflect the underlying semantics of web services by utilizing the terms within WSDL fully. The experiments show that our method works well on both service classification and query.