AbstractWe present OntoScene, a framework aimed at understanding the semantics of visual scenes starting from the semantics of their elements and the spatial relations holding between them. OntoScene exploits ontologies for representing knowledge and Prolog for specifying the interpretation rules that domain experts may adopt, and for implementing the SceneInterpreter engine. Ontologies allow the designer to formalize the domain in a reusable way and make the system modular and interoperable with existing multiagent systems, while Prolog provides a solid basis to define complex rules of interpretation in a way that can be affordable even for people with no background in Computational Logics. The domain selected for experimenting OntoScene is that of prehistoric rock art, which provides us with a fascinating and challenging testbed.
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.358 Gioseffi M. and Locoro A.. Two Sides of a Coin -Translate while Classify Multilanguage Annotations with Domain Ontology-driven Word Sense Disambiguation.
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