Web Services Clustering Using a Bio-inspired Algorithm

Abstract

In this work we describe a bio-inspired algorithm for Web service clustering, in particular we present an adaptation of the Ant Colony Optimization (ACO) algorithm which is applied over a collection of Web service descriptions. The adapted ACO uses input and output parameter definitions to calculate semantic similarity measures between all the different Web services. A set of experiments were carried out with promising results that show the benefits of the ACO algorithm for Web services clustering.