感觉系统
仿形(计算机编程)
感官分析
计算机科学
集合(抽象数据类型)
人工智能
模式识别(心理学)
数据挖掘
情报检索
数学
心理学
认知心理学
统计
操作系统
程序设计语言
作者
Eric Teillet,A. Thomas,L. Demonteil
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2023-01-01
卷期号:: 237-256
标识
DOI:10.1016/b978-0-12-821936-2.00008-x
摘要
Polarized sensory positioning (PSP) is an approach used to enable data aggregation from several studies. It consists of rating the similarity (or dissimilarity) of samples compared to a set of fixed samples references, called ``poles''. As such, it relies on a very natural way to describe things—objects or concepts—by comparing them with standards or well-known references. PSP was originally developed for easy definition of the sensory characteristics of drinking water without presenting too many samples. The method was then revealed to be applicable to various kinds of products (cosmetics, aromas, etc.) and appeared to be a good alternative to classical sensory profiling techniques. This chapter presents the PSP methodology, how to apply it in at least two different ways (Rating-PSP, Triad-PSP). Recommendations are given for the selection and the number of poles that should be used in a study. Suggestions are also given for the analysis of the new type of sensory data that are obtained using PSP. Eventually, this chapter presents four cases studies of application of PSP in the industry, including the use of PSP to determine the emotion map of a set of perfumes.
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