An automatic service classification approach

Abstract

With the development of the service technology, more and more organizations are publishing their business function as service through Internet. Service classification is a key approach for service management. With the quick increase of service number, the cost of classifying these services through manual work is becoming more and more expensive. A service automatic classification approach based on WordNet by combining text mining, semantic technology and machine learning technology was given in the paper. The method only relies on text description of services so that it can classify different type services, such as WSDL Web Service, RESTfulWeb Service and traditional network based software component service. Though text mining and applying word sense disambiguation models, a service can be described as a sense vector with no ambiguous. Then a K-means algorithm is used to classify these services. Experimental evaluations show that our classification method has good precision and recall. © 2011 Springer-Verlag Berlin Heidelberg.