Stochastic behavior, critical phenomena and rhythmic patterns identification in na...
Representation of a micro-thesaurus using SKOS: a methodological study
CogBot: integrating perceptual information and semantic knowledge in cognitive rob...
Grant number: | 18/11255-3 |
Support Opportunities: | Scholarships abroad - Research |
Start date: | October 03, 2018 |
End date: | April 02, 2019 |
Field of knowledge: | Linguistics, Literature and Arts - Linguistics - Linguistic Theory and Analysis |
Principal Investigator: | Marcos Fernando Lopes |
Grantee: | Marcos Fernando Lopes |
Host Investigator: | Christian Freksa |
Host Institution: | Faculdade de Filosofia, Letras e Ciências Humanas (FFLCH). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
Institution abroad: | University of Bremen, Germany |
Abstract Qualitative Spatial Reasoning (QSR) is a subfield of Artificial Intelligence that addresses the formal knowledge representation of spatial problems without relying on measures, coordinates, or numeric models, just on symbolic mapping of expressions and logic calculi, so it often relates to linguistic semantics and computational linguistics. This project presents a semantic-computational inquiry into spatiality in natural language utterances in order to put forth both descriptive and inferential models capable of rendering a qualitative calculus for the deictic perspective, which is one of the most commonly used perspective systems in conversational contexts. With a formal ontology of spatial objects embedded, this calculus should be easily integrated to Natural Language Inference algorithms. Theoretical foundations of spatial relations representations such as the figure / ground distinction and perspectives systems are discussed and a fragment of the deictic perspective calculus is introduced. | |
News published in Agência FAPESP Newsletter about the scholarship: | |
More itemsLess items | |
TITULO | |
Articles published in other media outlets ( ): | |
More itemsLess items | |
VEICULO: TITULO (DATA) | |
VEICULO: TITULO (DATA) | |