Intelligent sensory evaluation of industrial products for exploiting consumer's preference

This paper presents an intelligent technique based method for analyzing and interpreting sensory data provided by consumers and experts in order to predict consumer's preference on industrial products. In this study, we first introduce the concept of equilibrium consumption for estimating consumer's data variation between two different samples. This method can effectively solve the multi-peaks problem and the order correlation problem existing in consumer's data. According to the degree of consistency of data variation, we define the dissimilarities or distances between different evaluation terms used by consumers. Based on these dissimilarities, we develop a procedure for interpreting consumer's terms using normalized expert's evaluation terms. This procedure can also be used for predicting consumer's evaluation and preference from expert's evaluation on a collection of industrial products. The effectiveness of this method has been validated in one collection of cosmetic protection creams.