Computing the Data Semantics of WSDL Specifications via Gradient Boosting

Authors:
Alexandros G. Valarakos;George A. Vouros
Affiliations:
AI Lab, Information and Communication Systems Eng., Dept University of the Aegean, Samos, 83 200, Greece, {alexv, georgev}@ aegean.gr;AI Lab, Information and Communication Systems Eng., Dept University of the Aegean, Samos, 83 200, Greece, {alexv, georgev}@ aegean.gr
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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Abstract

This paper proposes a method for the semi-automatic semantic annotation of WSDL specifications, given ontologies related to the domain of services. The proposed method uses a synthesis of mapping methods to map input/output messages' parameters to ontology classes. Exploiting validated results provided by humans, the method learns via the gradient boosting learning algorithm to combine the individual mapping methods towards improving its accuracy. The aim is to mitigate difficulties concerning mappings and address limitations of other approaches, even in challenging cases, so as to assist human annotators to perform their work. The paper presents experimental results of the proposed methods.