Modelos causales como ayuda a la comprensión de sistemas complejos: Análisis de los factores críticos de éxito en el desarrollo de chatbots

Miguel Ángel Quiroz Martínez; Joseline  Mora Mora; Julissa  Medina Gruezo; Maikel Yelandi Leyva Vázquez

Modelos causales como ayuda a la comprensión de sistemas complejos: Análisis de los factores críticos de éxito en el desarrollo de chatbots

Miguel Ángel Quiroz Martínez, Joseline Mora Mora, Julissa Medina Gruezo, Maikel Yelandi Leyva Vázquez

Grupo de Investigación en Inteligencia Artificial y Reconocimiento Facial (GIIAR)

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

2 Citas (Scopus)

Resumen

We analyzed the factors that are considered key when developing chatbots, making the implementation effective and efficient; that is, that it achieves the objective for which it is created. The analysis was carried out using research techniques such as interviews with experts in chatbots development. The deductive method was used to analyse the information of the referenced articles. With the help of causal models and fuzzy cognitive maps it was possible to deduce and know how the factors affect each of the proposed scenarios.

Título traducido de la contribución	Causal models as an aid to understanding complex systems: Analysis of critical success factors in the development of chatbots
Idioma original	Español
Páginas (desde-hasta)	64-72
Número de páginas	9
Publicación	Universidad y Sociedad
Volumen	12
N.º	4
Estado	Publicada - 2020

Nota bibliográfica

Publisher Copyright:
© 2020, University of Cienfuegos, Carlos Rafael Rodriguez. All rights reserved.

Palabras clave

Causality
Chatbots
Covid-19
Critical success factors
Fuzzy cognitive maps

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Modelos causales como ayuda a la comprensión de sistemas complejos: Análisis de los factores críticos de éxito en el desarrollo de chatbots. / Quiroz Martínez, Miguel Ángel; Mora Mora, Joseline ; Medina Gruezo, Julissa et al.
En: Universidad y Sociedad, Vol. 12, N.º 4, 2020, p. 64-72.

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

TY - JOUR

T1 - Modelos causales como ayuda a la comprensión de sistemas complejos

T2 - Análisis de los factores críticos de éxito en el desarrollo de chatbots

AU - Quiroz Martínez, Miguel Ángel

AU - Mora Mora, Joseline

AU - Medina Gruezo, Julissa

AU - Leyva Vázquez, Maikel Yelandi

PY - 2020

Y1 - 2020

N2 - We analyzed the factors that are considered key when developing chatbots, making the implementation effective and efficient; that is, that it achieves the objective for which it is created. The analysis was carried out using research techniques such as interviews with experts in chatbots development. The deductive method was used to analyse the information of the referenced articles. With the help of causal models and fuzzy cognitive maps it was possible to deduce and know how the factors affect each of the proposed scenarios.

AB - We analyzed the factors that are considered key when developing chatbots, making the implementation effective and efficient; that is, that it achieves the objective for which it is created. The analysis was carried out using research techniques such as interviews with experts in chatbots development. The deductive method was used to analyse the information of the referenced articles. With the help of causal models and fuzzy cognitive maps it was possible to deduce and know how the factors affect each of the proposed scenarios.

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KW - Chatbots

KW - Covid-19

KW - Critical success factors

KW - Fuzzy cognitive maps

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SN - 2415-2897

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Modelos causales como ayuda a la comprensión de sistemas complejos: Análisis de los factores críticos de éxito en el desarrollo de chatbots

Resumen

Nota bibliográfica

Palabras clave

Otros archivos y enlaces

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