Sánchez-Gómez, Claudia
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Preferred name
Sánchez-Gómez, Claudia
Official Name
Sánchez Gómez, Claudia Nallely
Alternative Name
cnsanchez
Main Affiliation
ORCID
Scopus Author ID
57201851558
Researcher ID
DTU-3417-2022

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A comparative analysis of finite element programs for their implementation in a graphic tool of insulated power cables

2017 , Gutiérrez, Sebastián , Sánchez-Gómez, Claudia , Jeronimo Alvarez , Domínguez-Soberanes, Julieta

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Facial Emotion Recognition: A Comparison of Different Landmark-Based Classifiers

2018 , Álvarez-Pato, Víctor M. , Sánchez-Gómez, Claudia , Gutiérrez, Sebastián , Domínguez-Soberanes, Julieta , Velázquez, Ramiro

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Landscape images distance using kullback leibler divergence

2018 , Sánchez-Gómez, Claudia , Mario Graff , Domínguez-Soberanes, Julieta , Gutiérrez, Sebastián

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Selecting crackling product based on sensory analysis by different statistical data approaches

2017 , G. Sanchez-Gutierrez , Domínguez-Soberanes, Julieta , G. Rodriguez-Serrano , H. Escalona-Buendia , Sánchez-Gómez, Claudia , Gutiérrez, Sebastián , Mario Graff

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Consumer Acceptances Through Facial Expressions of Encapsulated Flavors Based on a Nanotechnology Approach

2018 , Álvarez-Pato, Víctor M. , Domínguez-Soberanes, Julieta , Sánchez-Gómez, Claudia , Gutiérrez, Sebastián , Bryan Lopez , Rodrigo Quiroz , David E. Mendoza , Hector E. Buendia , Velázquez, Ramiro

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Liking Product Landscape: Going Deeper into Understanding Consumers’ Hedonic Evaluations

2019 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Héctor B. Escalona-Buendía , Mario Graff , Gutiérrez, Sebastián , Gabriela Sánchez

The use of graphical mapping for understanding the comparison of products based on consumers’ perceptions is beneficial and easy to interpret. Internal preference mapping (IPM) and landscape segmentation analysis (LSA) have successfully been used for this propose. However, including all the consumers’ evaluations in one map, with products’ overall liking and attributes’ perceptions, is complicated; because data is in a high dimensional space some information can be lost. To provide as much information as possible, we propose the liking product landscape (LPL) methodology where several maps are used for representing the consumers’ distribution and evaluations. LPL shows the consumers’ distribution, like LSA, and also it superimposes the consumers’ evaluations. However, instead of superimposing the average overall liking in one map, this methodology uses different maps for each consumer’s evaluation. Two experiments were performed where LPL was used for understanding the consumers’ perceptions and compared with classic methodologies, IPM and cluster analysis, in order to validate the results. LPL can be successfully used for identifying consumers’ segments, consumers’ preferences, recognizing perception of product attributes by consumers’ segments and identifying the attributes that need to be optimized.

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