Structure Matching for Enhancing UDDI Query Results

To enhance UDDI query capability, typically based on taxonomic classification, semantic matching is assuming a key role. Even if we recognize the great importance of semantics in the discovery process, structure-based matching can be very useful in many situations where semantic annotations are not provided at publish time or ontologies are not yet well defined. Moreover, structure matching has a potential application in dynamic binding and invocation to perform correct parameter passing based on syntactic elements obtained from the mapping returned by the structure matching algorithm. The paper discusses the problem of similarity structure matching and proposes and compares different implementations of the algorithm introduced by Wang-Stroulia with the aim of obtaining better performance. We integrated the algorithm in a matchmaking framework based on multiple cascade filters that are able to combine several matchmaking techniques in order to improve precision and recall in a flexible and effective way.