TY - JOUR
T1 - Intelligent sensory evaluation: Concepts, implementations,and applications
AU - Zeng, Xianyi
AU - Ruan, Da
AU - Koehl, Ludovic
A2 - Laes, Erik
N1 - Score = 10
PY - 2008/5/1
Y1 - 2008/5/1
N2 - Sensory evaluation has been widely applied in different industrial fields especially for quality inspection, product design and marketing. Classically, factorial multivariate methods are the only tool for analyzing and modeling sensory data provided by experts, panelists or consumers. These methods are efficient for solving some problems but sometimes cause important information lost. In this situation, new methods based on intelligent techniques such as fuzzy logic, neural networks, data aggregation, classification, clustering have been applied for solving uncertainty and imprecision related to sensory evaluation. These new methods can be used together with the classical ones in a complementary way for obtaining relevant information from sensory data. This paper outlines the general background of sensory evaluation and the corresponding industrial interests and explicitly indicates some orientations for further development by IT researchers.
AB - Sensory evaluation has been widely applied in different industrial fields especially for quality inspection, product design and marketing. Classically, factorial multivariate methods are the only tool for analyzing and modeling sensory data provided by experts, panelists or consumers. These methods are efficient for solving some problems but sometimes cause important information lost. In this situation, new methods based on intelligent techniques such as fuzzy logic, neural networks, data aggregation, classification, clustering have been applied for solving uncertainty and imprecision related to sensory evaluation. These new methods can be used together with the classical ones in a complementary way for obtaining relevant information from sensory data. This paper outlines the general background of sensory evaluation and the corresponding industrial interests and explicitly indicates some orientations for further development by IT researchers.
KW - Sensory evaluation
KW - Fuzzy logic
KW - Data aggregation
KW - Classification
KW - Clustering
KW - Uncertainty
UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_88123
UR - http://knowledgecentre.sckcen.be/so2/bibref/4941
U2 - 10.1016/j.matcom.2007.11.013
DO - 10.1016/j.matcom.2007.11.013
M3 - Article
SN - 0378-4754
VL - 77
SP - 443
EP - 452
JO - Mathematics and Computers in Simulation
JF - Mathematics and Computers in Simulation
IS - 5-6
ER -