Making Sense out of Food

Brent Kievit-KylarCognitive Science Program, Indiana University
Peter ToddCognitive Science Program, Indiana University
Yong-Yeol AhnSchool of Informatics and Computing, Indiana University

Abstract

In this paper we explore the application of a novel data collection scheme for multi-sensory information to the question of whether different sensory domains tend to show similar relations between objects (along with some unique variance). Our analyses—hierarchical clustering, MDS mapping, and other comparisons between sensory domains—support the existence of common representational schemes for food items in the olfactory, taste, visual, and tactile domains. We further show that the similarity within different sensory domains is a predictor for Rosch (1975) typicality measures. We also use the relative importance of sensory domains to predict the overall similarity between pairs of words, and compare subjective similarities to objective similarities based on physical sensory properties of the foods, showing a reasonable match.

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Making Sense out of Food (656 KB)



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