Service retrieval based on hybrid SLVM of WSDL

ABSTRACT

Two practicable approaches were proposed for Web service retrieval, bipartite-graph matching and KbSM. But their models and similarity metrics of WSDL analysis may ignore some term or semantic feature, and involve formal method problem of representation or difficulty of parameter verification. SLVM and its improved model depend on statistical term measures to implement XML document representation. As a result, they ignore the lexical semantics and the distilled mutual information, leading to text analysis errors. This work proposed a service retrieval method, hybrid SLVM of WSDL, to address the problem of feature extraction. Using WordNet, this method constructed a lexical semantic spectrum to characterize the lexical semantics, and built a special term spectrum based on TF-IDF. Then, feature matrix for WSDL representation was built in the hybrid SLVM. Applying to NWKNN algorithm, on OWLS-TC version 2 dataset, the experimental results show that the feature matrix of our method performs F1 measure and query precisions better than bipartite-graph matching and KbSM.

References

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Index Terms

• Human-centered computing

  • Collaborative and social computing

    • Collaborative and social computing systems and tools

• Information systems

  • World Wide Web