Web service selection based on ranking of QoS using Naïve Bayes through ontology mapping

Web Services are a new kind of web application that has brought out quite challenging research issues. As the popularity of Web services increases, automated efficient discovery is desired. Due to the lack of representation of semantics in the description of Web services with the existing description languages, the process of selection could not retrieve the relevant Web services considering the QoS requirement of the application. Thus it is necessary to describe Web services more semantically. This work aims at proposing a model for Web service selection using Naïve Bayes for ranking of QoS by utilizing the ontology mapping pattern. In detail, this work selects the relevant and proficient Web service using Naïve Bayes theory by applying ranking algorithm for QoS functionalities of each service given by service providers. Initially Mapped Meta Information (MMI) in XML format is generated using ontology mapping for specific web service as per consumer´s requirements. This combined approach would give more and more accurate Web service selection to consumers for their need.