What is it about?
In this paper we present a framework that instantiates cognitive agents operating in IoT context, endowed with meta-reasoning in the Semantic Web. The framework, called SW-Caspar, is also provided with a module that performs semi-automatic ontology learning from sentences expressed in natural language; such a learning process generates a conceptual space reflecting the domain of discourse with an instance of a novel foundational ontology called Linguistic Oriented Davidsonian Ontology (LODO), whose main feature is to increase the deepness of reasoning without compromising linguistic-related features. LODO is inspired by the First-Order Logic Davidsonian notation and serialized in OWL 2.
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Why is it important?
Our aim is to facilitate or allow (where not possible) the interoperability among IoT agents, by leveraging also human fashioned meta-reasoning in the Semantic Web, in order to istantiate cognitive agents.
Perspectives
The LODO ontologies are built with a semi-automatic process, taking into account the issues of natural language ontology, in order to fill the gap between expressiveness and human-like fashioned reasoning.
Carmelo Fabio Longo
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This page is a summary of: Towards ontological interoperability of cognitive IoT agents based on natural language processing¶, Intelligenza Artificiale, July 2022, IOS Press,
DOI: 10.3233/ia-210125.
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