Service discovery and matchmaking in a distributed environment has been an active research issue for some time now. Previous work on matchmaking has typically presented the problem and service descriptions as free or structured (marked-up) text, so that keyword searches, tree-matching or simple constraint solving are sufficient to identify matches. In this paper, we discuss the problem of matchmaking for mathematical services, where the semantics play a critical role in determining the applicability or otherwise of a service and for which we use OpenMath descriptions of pre-and post-conditions. We describe a matchmaking architecture supporting the use of match plug-ins and describe five kinds of plug-in that we have developed to date: (i) A basic structural match, (ii) a syntax and ontology match, (iii) a value substitution match, (iv) an algebraic equivalence match and (v) a decomposition match. The matchmaker uses the individual match scores from the plug-ins to compute a ranking by applicability of the services. We consider the effect of pre-and post-conditions of mathematical service descriptions on matching, and how and why to reduce queries into Disjunctive Normal Form (DNF) before matching. A case study demonstrates in detail how the matching process works for all four algorithms.
Service description and discovery offer complementary challenges, but in both cases, the problem is finding the right trade-off between accuracy and generality that will result in a positive service identification. Discovery systems have historically tended to focus on domain-specific techniques using single sources of knowledge to help classify queries against services, making both maintenance and extension difficult. The primary contribution of this paper is the presentation of a generic brokerage framework based on the use of plug-in components, that are themselves web services. The framework has been developed in the context of the KNOOGLE project, where the focus has been on demonstrating support for (i) the discovery of Grid services for the GridSAM job submission system and (ii) integration with the Taverna workflow enactment system. However, the broker itself is domain independent and it is the multiple user-specified matchmaker plug-ins that act as sources of domain-specific knowledge. The broker collects the results of the matchmakers' comparison of the query and service and then applies a user-specified selection policy to determine the final choice of service. Thus a range of comprehensive packaging of brokerage functionality becomes possible through the use of supplied and user-defined matchers and supplied or user-defined selection policies.Third IEEE International Conference on e-Science and Grid Computing 0-7695-3064-8/07 $25.00
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.