Calculating word similarity for context aware web service clustering

Web service discovery is becoming difficult task because of increasing Web services available on the Internet. Therefore, organizing the Web services into functionally similar clusters is very efficient approach now. In order to cluster web service, each context are need to categorized own domain. Current works for service clustering have not considered the context. To make clustering of web services by domain context, we need calculation of terms similarity under a specific context. We first use support vector machine to learn context in a domain and web search engine to classify terms to domain. In this paper, we suggest a novel method to measure terms similarity consider the specific domain context using machine learning for efficient clustering.