MINING MEANING OF WEB SERVICES

Abstract

Web services have been evolved as a versatile and cost effective solution for exchanging dissimilar data between distributed applications. They have become a fundamental part of service oriented architecture (SOA). The most challenging problem being faced by service oriented architecture is to figure out what a service does and how to use its capabilities without direct negotiation with service provider. Discovering and exploring web services registered with UDDI registry or Web Services-Inspection (WS-Inspection) documents requires exact search criteria such as service category, service name and service URL. This study focuses on creating a smarter automated web service classification technique by applying Maximum Entropy machine learning algorithm to attributes of Web Service Description language (WSDL) documents. WSDL document allows web services clients to learn operations, communication protocols and correct message format of service. Manually analyzing WSDL documents is the best approach but most expensive. Therefore a text mining based approach is suggested for classifying web services into functional groups.