A novel method for semantic web services discovery

The discovery of suitable web services for a given task is one of the major operations in SOA architecture, and researches are beingdone to automate this step. For the large amount of available Web services that can be expected in real-world settings, the computational costs ofautomated discovery based on semantic matchmaking become important. To make a discovery engine a reliable software component, we mustaim at minimizing both the mean and the variance of the duration of the discovery task. For this, we present an extension for discovery enginesin SWS environments that exploit structural knowledge and previous discovery results for reducing the search space of consequent discoveryoperations. Our prototype implementation shows significant improvements when applied to the Stanford SWS Challenge scenario and dataset.