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AgreementMakerLight (AML) is an automated ontology matching framework based on element-level matching and the use of external resources as background knowledge. This paper describes the configuration of AML for the OAEI 2014 competition and discusses its results. Our goal this year was broadening the scope of AML by delving into aspects such as translation(More)
The i* framework cannot effectively model crosscutting concerns, compromising modularity, reusability and evolution of the results. Our approach embodies a specific notation to represent and compose aspectual i* models, using aspect-orientation to address modularity and composition of crosscutting concerns. This represents a step forward to improve(More)
Requirements engineering and architectural design are key activities for successful development of software systems. Both activities are strongly intertwined and interrelated, but many steps toward generating architecture models from requirements models are driven by intuition and architectural knowledge. Thus, systematic approaches that integrate(More)
Ideally, all system failures should be compensated. In fact, most failure-prone systems try to compensate all their failures. However, sometimes a compensation is not essential. Hence, diagnosing and compensating each and every one of their failures may be ineffective. Thus, this work aims to increase the flexibility of failure handling in self-configuring(More)
AgreementMaker is one of the leading ontology matching systems, thanks to its combination of a flexible and extensible framework with a comprehensive user interface. In many domains, such as the biomedical, ontologies are becoming increasingly large thus presenting new challenges. We have developed a new core framework, Agreement-MakerLight, focused on(More)
Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of(More)
Good business processes need to be up-to-date and automated to represent the organizational environment. To obtain models that reflect the changes it is necessary continuous checking between model and reality. Thus, business process model need to be modifiable and transformable in software. In order satisfy these needs we propose to apply variability(More)