The Web is transforming from a Web of data to a Web of both Semantic data and services. This trend is providing us with increasing opportunities to compose potentially interesting and useful services from existing services. While we may not sometimes have the specific queries needed in top-down service composition approaches to identify them, the early and proactive exposure of these opportunities will be key to harvest the great potential of the large body of Web services. In this paper, we propose a Web service mining framework that allows unexpected and interesting service compositions to automatically emerge in a bottom-up fashion. We present several mining techniques aiming at the discovery of such service compositions. We also present evaluation measures of their interestingness and usefulness. As a novel application of this framework, we demonstrate its effectiveness and potential by applying it to service-oriented models of biological processes for the discovery of interesting and useful pathways.
['George Zheng', 'Athman Bouguettaya']
Service Mining on the Web