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ASSAM: A Tool for Semi-Automatically Annotating ... - CiteSeerX

ASSAM: A Tool for Semi-Automatically Annotating ... - CiteSeerX

ASSAM: A Tool for Semi-Automatically Annotating ... -

ASSAM: A Tool for Semi-Automatically Annotating Semantic Web Services Andreas Heß, Eddie Johnston, and Nicholas Kushmerick Computer Science Department, University College Dublin, Ireland {andreas.hess, eddie.johnston, nick}@ucd.ie Abstract. The semantic Web Services vision requires that each service be annotated with semantic metadata. Manually creating such metadata is tedious and error-prone, and many software engineers, accustomed to tools that automatically generate WSDL, might not want to invest the additional effort. We therefore propose ASSAM, a tool that assists a user in creating semantic metadata for Web Services. ASSAM is intended for service consumers who want to integrate a number of services and therefore must annotate them according to some shared ontology. ASSAM is also relevant for service producers who have deployed a Web Service and want to make it compatible with an existing ontology. ASSAM’s capabilities to automatically create semantic metadata are supported by two machine learning algorithms. First, we have developed an iterative relational classification algorithm for semantically classifying Web Services, their operations, and input and output messages. Second, to aggregate the data returned by multiple semantically related Web Services, we have developed a schema mapping algorithm that is based on an ensemble of string distance metrics. 1 Introduction The vision of semantic Web Services is to provide the means for fully automated discovery, composition and invocation of loosely coupled software components. One of the key efforts to address this “semantic gap” is the well-known OWL-S ontology [1]. However, software engineers who are developing Web Services usually do not think in terms of ontologies, but rather in terms of their programming tools. Existing tools for both the Java and .NET environments support the automatic generation of WSDL. We believe that it would boost the semantic service web if similar tools existed to (semi-) automatically generate OWL-S or a similar form of semantic metadata. In this paper we will present a tool called ASSAM—Automated Semantic Service Annotation with Machine Learning—that addresses these needs. AS- SAM consists of two parts, a WSDL annotator application, and OATS, a data aggregation algorithm. We describe the WSDL annotator application in Sec. 2. This component of ASSAM uses machine learning to provide the user with suggestions on how to

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