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A Fuzzy Ontology for Semantic Modelling and Recognition of Human Behaviour

Natalia Díaz Rodríguez, Manuel Pegalajar Cuéllar, Johan Lilius, Miguel Delgado Calvo-Flores, A Fuzzy Ontology for Semantic Modelling and Recognition of Human Behaviour. Knowledge-Based Systems 66, 46–60, 2014.

http://dx.doi.org/10.1016/j.knosys.2014.04.016

Abstract:

We propose a fuzzy ontology for human activity representation, which allows us to model and reason about vague, incomplete, and uncertain knowledge. Some relevant subdomains found to be missing in previous proposed ontologies for this domain were modelled as well. The resulting fuzzy OWL 2 ontology is able to model uncertain knowledge and represent temporal relationships between activities using an underlying fuzzy state machine representation. We provide a proof of concept of the approach in work scenarios such as the office domain, and also make experiments to emphasize the benefits of our approach with respect to crisp ontologies. As a result, we demonstrate that the inclusion of fuzzy concepts and relations in the ontology provide benefits during the recognition process with respect to crisp approaches.

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BibTeX entry:

@ARTICLE{jDxCuLiDe14a,
  title = {A Fuzzy Ontology for Semantic Modelling and Recognition of Human Behaviour},
  author = {Díaz Rodríguez, Natalia and Pegalajar Cuéllar, Manuel and Lilius, Johan and Delgado Calvo-Flores, Miguel},
  journal = {Knowledge-Based Systems},
  volume = {66},
  publisher = {Elsevier},
  pages = {46–60},
  year = {2014},
  keywords = {fuzzy ontologies, activity recognition, ambient assisted living, ambient intelligence},
  ISSN = {0950-7051},
}

Belongs to TUCS Research Unit(s): Embedded Systems Laboratory (ESLAB)

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