Using SVM and Concept Analysis to support Web Service Classification and Annotation

The need for supporting the classification and semantic anno t tion of services constitutes an important challenge for service –centric software engineering. Late–binding and, in general, servi c matching approaches, require services to be semantically annota ted. Such a semantic annotation may require, in turn, to be made in agre ement to a specific ontology. Also, a service description needs to p roperly relate with other similar services. This paper proposes an approach to i) automatically classif y ervices to specific domains and ii) identify key concepts insid e service textual documentation, and build a lattice of relation ships between service annotations. Support Vector Machines and For mal Concept Analysis have been used to perform the two tasks. Res ults obtained classifying a set of web services show that the appr o ch can provide useful insights in both service publication and service retrieval phases.