A knowledge-based system for prototypical reasoning

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 framework). 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.

Geometric analysis of concept vectors based on similarity values

“…The similarity of two entities is defined as a function of the distance between two points in the space. There are some implementations of conceptual spaces, while some in knowledge representation and reasoning (Frixione and Lieto 2013;Gärdenfors and Williams 2001;Lieto et al 2015), others in spatial information systems (Adams and Raubal 2009;Janowicz et al 2012;Raubal 2004). …”

A Resource-Driven Approach for Anchoring Linguistic Resources to Conceptual Spaces

“…The input to the system is a simple sentence, like 'The feline with mane and big jaws', and the correct output is the category evoked by the description (the category lion in this case). 13 Correctly identified categories represent a gold standard which has been individuated based on the results of an experiment involving human subjects [28]; both outputs have thus been compared to human answers.…”

“…In particular, a target concept illustrated by a simple common-sense linguistic description had to be identified; for this experiment we exploited an existing categorization system that relies on a hybrid knowledge base coupling annotated Conceptual Spaces encoding common-sense information, and an external ontological component, represented by the OpenCyc ontology [28,29,30]. In this evaluation we compared the output provided by this system in two different executions: in the former case the categorization system made use of manually annotated Conceptual Spaces, whilst in the latter one it was fed with the Conceptual Spaces extracted by the TTCS system.…”

MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach

“…The CSs framework has been recently used to extend and complement the representational and inferential power allowed by formal ontologies with special emphasis on dealing with the corresponding typicality-based conceptual reasoning (Lieto et al, 2015; in this setting, the TTCS E aims at providing a wide-coverage, cognitively based linguistic resource for this sort of knowledge, by extending previous work (Lieto et al, 2016;Mensa et al, 2017).…”