Algorithms for clustering data
Algorithms for clustering data
On automating Web services discovery
The VLDB Journal — The International Journal on Very Large Data Bases
Automated semantic web service discovery with OWLS-MX
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Automatic Matchmaking of Web Services
ICWS '06 Proceedings of the IEEE International Conference on Web Services
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Investigating web services on the world wide web
Proceedings of the 17th international conference on World Wide Web
Distributed automatic service composition in large-scale systems
Proceedings of the second international conference on Distributed event-based systems
Web service clustering using text mining techniques
International Journal of Agent-Oriented Software Engineering
WSExpress: A QoS-aware Search Engine for Web Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Clustering WSDL Documents to Bootstrap the Discovery of Web Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Measuring Similarity of Web Services Based on WSDL
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
The construction of domain ontology and its application to document retrieval
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Titan: a system for effective web service discovery
Proceedings of the 21st international conference companion on World Wide Web
Automated Tagging for the Retrieval of Software Resources in Grid and Cloud Infrastructures
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Sparse functional representation for large-scale service clustering
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
WSTRank: ranking tags to facilitate web service mining
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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Clustering web services would greatly boost the ability of web service search engine to retrieve relevant ones. An important restriction of traditional studies on web service clustering is that researchers focused on utilizing web services' WSDL (Web Service Description Language) documents only. The singleness of data source limits the accuracy of clustering. Recently, web service search engines such as Seekda! allow users to manually annotate web services using so called tags, which describe the function of the web service or provide additional contextual and semantical information. In this paper, we propose a novel approach called WTCluster, in which both WSDL documents and tags are utilized for web service clustering. Furthermore, we present and evaluate two tag recommendation strategies to improve the performance of WTCluster. The comprehensive experiments based on a dataset consists of 15,968 real web services demonstrate the effectiveness of WTCluster and tag recommendation strategies.