Análisis de Canasta de mercado en supermercados mediante mapas auto-organizados

Authors

DOI:

https://doi.org/10.5380/atoz.v10i3.81491

Keywords:

SOM, Análisis de canasta de compra, Python, Minería de Datos, Redes Neuronales

Abstract

Introducción: Una cadena importante de supermercados de la zona poniente de la capital de Chile, necesita obtener información clave para tomar decisiones. Esta información se encuentra disponible en las bases de datos, pero necesita ser procesada debido a la complejidad y cantidad de información, lo que genera una dificultad a la hora de visualizar. Método: Para este propósito, se ha desarrollado un algoritmo que utiliza redes neuronales artificiales, aplicando el método SOM de Kohonen. Para llevarlo a cabo, se han debido seguir ciertos procedimientos claves, como preparar la información, para luego utilizar solo los datos relevantes a las canastas de compra de la investigación. Luego de efectuado el filtrado, se tiene que preparar el ambiente de programación en Python para adaptarlo a los datos de la muestra, y luego proceder a entrenar el SOM con sus parámetros fijados luego de resultados de pruebas. Resultado: El resultado del SOM obtiene la relación entre los productos que más se compraron, posicionándolos topológicamente cerca, para conformar promociones y bundles, para que el retail mánager tome en consideración. Conclusión: En base a esto, se han hecho recomendaciones sobre canastas de compra frecuentes a la cadena de supermercados que ha proporcionado los datos utilizados en la investigación.

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Published

2021-11-08

How to Cite

Cordero Lustig, J. I., Bolt, A., & Valle, M. A. (2021). Análisis de Canasta de mercado en supermercados mediante mapas auto-organizados. AtoZ: Novas práticas Em informação E Conhecimento, 10(3), 1–11. https://doi.org/10.5380/atoz.v10i3.81491

Issue

Vol. 10 No. 3 (2021): sep./dec.

Section

Thematic Issue - Article

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