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

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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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Night club recommendation system based on decision trees

2021 , Sánchez-Gómez, Claudia , Jose-Carlos Delgado-Gomez , Pablo Ramirez-Espana , Luis Garcia-Zermeno , Samantha Licea , Domínguez-Soberanes, Julieta

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A Multisensor Data Fusion Approach for Predicting Consumer Acceptance of Food Products

2020 , Álvarez-Pato, Víctor M. , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Mendoza Pérez, David Eduardo , Velázquez, Ramiro

Sensory experiences play an important role in consumer response, purchase decision, and fidelity towards food products. Consumer studies when launching new food products must incorporate physiological response assessment to be more precise and, thus, increase their chances of success in the market. This paper introduces a novel sensory analysis system that incorporates facial emotion recognition (FER), galvanic skin response (GSR), and cardiac pulse to determine consumer acceptance of food samples. Taste and smell experiments were conducted with 120 participants recording facial images, biometric signals, and reported liking when trying a set of pleasant and unpleasant flavors and odors. Data fusion and analysis by machine learning models allow predicting the acceptance elicited by the samples. Results confirm that FER alone is not sufficient to determine consumers’ acceptance. However, when combined with GSR and, to a lesser extent, with pulse signals, acceptance prediction can be improved. This research targets predicting consumer’s acceptance without the continuous use of liking scores. In addition, the findings of this work may be used to explore the relationships between facial expressions and physiological reactions for non-rational decision-making when interacting with new food products.

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Recommendation System for a Delivery Food Application Based on Number of Orders

2023 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Alejandra Arreola , Mario Graff

With the recent growth in food-delivery applications, creating new recommendation systems tailored to this platform is essential. State-of-the-art restaurant recommendation systems are based on users’ ratings or reviews, with data that are obtained from questionnaires or online platforms such as TripAdvisor, Zomato, Foursquare, or Yield. However, not all users give ratings or reviews after their purchase. This document proposes a recommendation system whose input is the number of orders stored by a real food-delivery application. These data are always available for all food-delivery applications and are stored all the time. Our proposal is based on the nearest-neighbor technique that calculates the client’s preferred restaurants and analyzes other clients with similar buying patterns. In addition, we propose a performance metric that can be used for this specific recommendation system that is based on real restaurant sales. We use a real dataset (available online) to validate our proposal. Based on our experiments, the recommendation system successfully gives only an average of 7.7 options from 187 that are available. We compared our proposal with other state-of-the-art recommendation techniques and obtained a better performance. Our results indicate that it is possible to generate recommendations based on the number of orders, making the use of a restaurant-recommendation system feasible in a real food-delivery application.

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Determinación de la aceptación de alimentos mediante reacciones fisiológicas del consumidor: un enfoque basado en aprendizaje automático

2021 , Domínguez-Soberanes, Julieta , Álvarez-Pato, Víctor M. , Sánchez-Gómez, Claudia , Mendoza Pérez, David Eduardo , Velázquez, Ramiro

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Analysis of Meat Color Change using Computer Vision

2020 , Gustavo Meza , Sánchez-Gómez, Claudia , Orvañanos-Guerrero, María T. , Domínguez-Soberanes, Julieta

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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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Physicochemical and Sensory Characteristics of Sausages Made with Grasshopper (Sphenarium purpurascens) Flour

2022 , Salvador O. Cruz-López , Yenizey M. Álvarez-Cisneros , Domínguez-Soberanes, Julieta , Héctor B. Escalona-Buendía , Sánchez-Gómez, Claudia

Insects are currently of interest due to their high nutritional value, in particular for the high concentration of quality protein. Moreover, it can also be used as an extender or binder in meat products. The objective was to evaluate grasshopper flour (GF) as a partial or total replacement for potato starch to increase the protein content of sausages and achieve good acceptability by consumers. GF has 48% moisture, 6.7% fat and 45% total protein. Sausages were analyzed by NIR and formulations with GF in all concentrations (10, 7, 5 and 3%) combined with starch (3, 5 and 7%) increased protein content. Results obtained for the sausages formulations with grasshoppers showed an increase in hardness, springiness, gumminess and chewiness through a Texture-Profile-Analysis. Moreover, a* and b* are similar to the control, but L* decreased. The check-all-that-apply test showed the attributes highlighted for sausages with GF possessed herbal flavor, brown color, and granular texture. The liking-product-landscape map showed that the incorporation of 7 and 10% of GF had an overall liking of 3.2 and 3.3, respectively, considered as “do not like much”. GF can be used as a binder in meat products up to 10% substitution. However, it is important to improve the overall liking of the sausage.

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Images dataset of beef meat samples with different shelf life

2023 , Domínguez-Soberanes, Julieta , Orvañanos-Guerrero, María T. , Sánchez-Gómez, Claudia , Maximiliano , Esteban García , Juan Pablo Cisneros , Luis Enrique Orozco , Ernesto Rosales-Tavera

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Heidegger and the simile of the cave. The assumptions of its interpretation

2020 , Domínguez-Soberanes, Julieta , Sánchez-Gómez, Claudia , Orvañanos-Guerrero, María T.

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