A knowledge-based system for prototypical reasoning. Minieri, A.; Lieto, A.; Piana, A.; and Radicioni, D. P. Connection Science, 27(2):137--152, Taylor & Francis, 2015.
doi  abstract   bibtex   
In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces frame- work). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorization task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning `conceptual' capabilities of standard ontology-based systems.
@article{lieto14knowledge,
	Abstract = {In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces frame- work). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorization task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning `conceptual' capabilities of standard ontology-based systems.},
	Author = {Minieri, Andrea and Lieto, Antonio and Piana, Alberto and Radicioni, Daniele P.},
	Date-Modified = {2015-06-03 14:03:29 +0000},
	Doi = {10.1080/09540091.2014.956292},
	Journal = {Connection Science},
	Number = {2},
	Pages = {137--152},
	Publisher = {Taylor & Francis},
	Title = {{A knowledge-based system for prototypical reasoning}},
	Volume = {27},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1080/09540091.2014.956292}}
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