Conceptual Spaces and Computing with Words

The purpose of this paper is to explore synergies and gaps in research in Conceptual Spaces (CS) and Computing with Words (CWW), which both attempt to address aspects of human cognition such as judgement and intuition. Both CS and CWW model concepts in term of collections of properties, and use similarity as a key computational device. We outline formal methods developed in CWW for modelling and manipulating constructs when membership values are imprecise. These could be employed in CS modelling. On the other hand, CS offers a more comprehensive theoretical framework than CWW for the construction of properties and concepts on collections of domains. We describe a specific formalism of CS based on fuzzy sets, and discuss problems with it and with alternative methods for aggregating property memberships into concept membership. To overcome the problems, we present a model in which all constructs are fuzzy sets on a plane, and similarity of two constructs is an inverse function of the average separation between their membership functions.

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