Case-Based Classification Alternatives to Ontologies for Automated Web Service Discovery and Integration

摘要

Web Services are becoming the standard technology used to share data for many Navy and other DoD operations. Since Web Services technologies provide for discoverable, self-describing services that conform to common standards, this paradigm holds the promise of an automated capability to obtain and integrate data. However, automated integration of applications to access and retrieve data from heterogeneous sources in a distributed system such as the Internet poses many difficulties. Assimilation of data from Web-based sources means that differences in schema and terminology prevent simple querying and retrieval of data. Thus, machine understanding of the Web Services interface is necessary for automated selection and invocation of the correct service. Service availability is also an issue that needs to be resolved. There have been many advances on ontologies to help resolve these difficulties to support the goal of sharing knowledge for various domains of interest. In this paper we examine the use of case-based classification as an alternative/supplement to using ontologies for resolving several questions related to knowledge sharing. While ontologies encompass a formal definition of a domain of interest, case-based reasoning is a problem solving methodology that retrieves and reuses decisions from stored cases to solve new problems, and case-based classification involves applying this methodology to classification tasks. Our approach generalizes well in sparse data, which characterizes our Web Services application. We present our study as it relates to our work on development of the Advanced MetOc Broker, whose objective is the automated application integration of meteorological and oceanographic (MetOc) Web Services.