Enhancing service discovery using cat swarm optimisation based web service clustering

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• 作者：Sunaina Kotekar ^{sunainakotekar@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Sowmya S. Kamath ; ^{sowmyakamath@nitk.ac.in" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Web service discovery ; WSDL ; CSO ; Clustering ; Swarm intelligence
• 刊名：Perspectives in Science
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：8
• 期：Complete
• 页码：715-717
• 全文大小：435 K

文摘

Web service discovery is a critical task in service oriented application development. Due to extensive proliferation in the number of available services, it is challenging to obtain all the relevant services available for a given task. For the retrieval of most relevant Web services, a user would have to use those service-specific terms that best describe and match the natural language documentation contained within a service description. This process can be time intensive, due to functional diversity of available services in a repository. Domain specific clustering of Web Services based on the similarities of their functionalities would greatly boost the ability of a Web service search engine to retrieve the most relevant service. In this paper, we propose a novel technique to cluster service documents into functionally similar service groups using the Cat Swarm Optimisation Algorithm. We present experimental results that show that the proposed technique was effective and enhanced the process of service discovery.