OntologyBeanGenerator 5.0: Extending ontology concepts with methods and exceptions

When modeling and implementing complex systems based on agents and artifacts, achieving semantic interoperability is not only useful, but often necessary. A commonly adopted solution to manage complex and real MASs is adopting a Model Driven methodology, which uses an ontology as the formal representation of the domain, and then exploiting some existing tool to automatically generate code for agents in the MAS, to let them interact according to the model. While this approach is satisfactorily supported when the target MAS environment is Jason, less support is provided to Jade MASs, despite Jade's large adoption for real MASs development. So, considering the great support given by the automatic code generation starting from a formal model, and the large community working on Jade MASs, in this work we present an extension of the OntologyBeanGenerator plugin for Prot\ue9g\ue9, used to generate a Java representation of an OWL ontology for Jade. We improved the OntologyBeanGenerator tool to support the modeling of exceptions, formalized at the ontology level, and of methods associated with ontology elements, to set the interface of concrete objects (artifacts) at design stage. This extension allows us to integrate in a Model Driven approach a support for the formal definition of artifacts and provide an automatic generation of Jade code/interfaces to interact with them respecting the model

Two sides of a coin: translate while classify multilanguage annotations with domain ontology-driven word sense disambiguation

In this paper we present an approach for the translation and classification of short texts in one step. Our work lays in the tradition of Domain-Driven Word Sense Disambiguation, though a major emphasis is given to domain ontologies as the right tool for sense-tagging and topic detection of short texts which, by their nature, are known to be reluctant to statistical treatment. We claim that in a scenario where users can annotate knowledge items using different languages, domain ontologies can prove very suitable for driving the word disambiguation and topic classification tasks. In this way, two tasks are gainfully collapsed in a single one. Although this study is still in its infancy, in what follows we are able to articulate motivations, design, workflow analysis, and concrete evolutions envisioned for our tool.15-18 February 201