On Flexible Web Services Composition Networks
This work addresses the challenge of improving syntactic Web services composition for developers and researchers, but it is incremental as it focuses on comparing existing metrics rather than introducing new methods.
The paper tackled the problem of syntactic Web services composition by building networks using three similarity metrics (Levenshtein, Jaro, Jaro-Winkler) and comparing their performance on real-world data, finding that Jaro-Winkler identifies more appropriate similarities at higher thresholds while Jaro is preferable at lower thresholds for reducing irrelevant relationships.
The semantic Web service community develops efforts to bring semantics to Web service descriptions and allow automatic discovery and composition. However, there is no widespread adoption of such descriptions yet, because semantically defining Web services is highly complicated and costly. As a result, production Web services still rely on syntactic descriptions, key-word based discovery and predefined compositions. Hence, more advanced research on syntactic Web services is still ongoing. In this work we build syntactic composition Web services networks with three well known similarity metrics, namely Levenshtein, Jaro and Jaro-Winkler. We perform a comparative study on the metrics performance by studying the topological properties of networks built from a test collection of real-world descriptions. It appears Jaro-Winkler finds more appropriate similarities and can be used at higher thresholds. For lower thresholds, the Jaro metric would be preferable because it detect less irrelevant relationships.