Efficient Measurement of Service Similarity

Abstract

The authors define a formal model for information services that incorporates the concept of service similarity. The model places services in metric spaces, and allows for services that have arbitrarily complex inputs and output domains. The authors then address the challenge of service substitution: finding the services most similar to a given service among a group, possibly large, of candidate services. To solve this nearest neighbor problem efficiently the authors embed the space of services into a vector space and search for the nearest neighbors in the target space. The authors report on an extensive experiment that validates both their formalization of similarity and their methods for finding service substitutions.