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
Titan: a system for effective web service discovery
Proceedings of the 21st international conference companion on World Wide Web
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
Sparse functional representation for large-scale service clustering
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
International Journal of Web Engineering and Technology
Efficient web service discovery using hierarchical clustering
AT'13 Proceedings of the Second international conference on Agreement Technologies
Modelling and exploring historical records to facilitate service composition
International Journal of Web and Grid Services
| Hi-index | 0.00 |
The increasing use of the Web for everyday tasks is making Web services an essential part of the Internet customer's daily life. Users query the Internet for a required Web service and get back a set of Web services that may or may not satisfy their request. To get the most relevant Web services that fulfill the user's request, the user has to construct the request using the keywords that best describe the user's objective and match correctly with the Web Service name or location. Clustering Web services based on function similarities would greatly boost the ability of Web services search engines to retrieve the most relevant Web services. This paper proposes a novel technique to mine Web Service Description Language (WSDL) documents and cluster them into functionally similar Web service groups. The application of our approach to real Web services description files has shown good performance for clustering Web services based on function similarity, as a predecessor step to retrieving the relevant Web services for a user request by search engines.