Proceedings of the Annual Meeting of the Cognitive Science Society

Property intercorrelations are viewed as central to the representation and processing of real-world object concepts. In contrast, prior research into real-world object concepts has incorporated the assumption that properties are independent and additive. In two studies, the role of correlated properties was explored. Property norms had been collected for 190 natural kinds and artifacts. In Experiment 1, property intercorrelations influenced performance in a property verification task. In Experiment 2, concept similarity, as measured by overlap of independent properties, predicted short interval priming latency for artifacts. In contrast, concept similarity, as measured by overlap of correlated property pairs, predicted short interval priming for natural kinds. The influence of property intercorrelations was stronger for natural kinds because they tended to contain a higher proportion of correlated properties. It was concluded that people encode knowledge about independent and correlated properties of real-world objects. Presently, a Hopfield netwoiic is being implemented to explore implications of allowing a system to encode property intercorrelations. Finally, results suggest that semantic relatedness can be defined in terms of property overlap between concepts.