An\'alisis de Canasta de mercado en supermercados mediante mapas auto-organizados
Joaqu\'in Cordero, Alfredo Bolt, Mauricio Valle

TL;DR
This paper presents a method using self-organizing maps to analyze supermarket shopping baskets, revealing product relationships for better marketing strategies based on real transaction data.
Contribution
It introduces a neural network-based approach for market basket analysis that visualizes product relationships in a topological map, aiding decision-making.
Findings
Identified product groupings based on purchase patterns
Enabled visualization of product relationships for marketing
Provided actionable recommendations for promotions
Abstract
Introduction: An important chain of supermarkets in the western zone of the capital of Chile, needs to obtain key information to make decisions, this information is available in the databases but needs to be processed due to the complexity and quantity of information which becomes difficult to visualiz,. Method: For this purpose, an algorithm was developed using artificial neural networks applying Kohonen's SOM method. To carry it out, certain key procedures must be followed to develop it, such as data mining that will be responsible for filtering and then use only the relevant data for market basket analysis. After filtering the information, the data must be prepared. After data preparation, we prepared the Python programming environment to adapt it to the sample data, then proceed to train the SOM with its parameters set after test results. Result: the result of the SOM obtains the…
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Taxonomy
TopicsAgricultural and Food Production Studies · Business, Innovation, and Economy
MethodsSelf-Organizing Map
