Algorithms for clustering data
Algorithms for clustering data
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
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
WTCluster: utilizing tags for web services clustering
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
A bottom-up, knowledge-aware approach to integrating and querying web data services
ACM Transactions on the Web (TWEB)
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With the increase of web services and user demand's diversity, effective web service discovery is becoming a big challenge. Clustering web services would greatly boost the ability of web service search engine to retrieve relevant ones. In this paper, we propose a web service search engine Titan which contains 15,969 web services crawled from the Internet. In Titan, two main technologies, i.e., web service clustering and tag recommendation, are employed to improve the effectiveness of web service discovery. Specifically, both WSDL (Web Service Description Language) documents and tags of web services are utilized for clustering, while tag recommendation is adopted to handle some inherent problems of tagging data, e.g., uneven tag distribution and noise tags.