Web Service Evolution, Linked Open Data, User Feedback, Composition, Substitution

International audienceWeb services are subject to changes during their lifetime, such as updates in data types, operations, and the overall function-ality. Such changes may impact the way Web services are discovered, consumed, and recommended. We propose a Linked Open Data (LOD) approach for managing Web services new deployment and updates. We propose algorithms, based on semantic LOD similarity measures, to infer composition and substitution relationships for both newly deployed and updated services. We introduce a technique that gathers Web service interactions and users' feedbacks to continuously update service relationships. To improve the accuracy of relationship recommendation, we propose an algorithm to learn new LOD relationships from Web service past interaction. We conduct extensive experiments on real-world Web services to evaluate our approach