Market Basket Analysis Using Boltzmann Machines

Mauricio A. Valle, Gonzalo A. Ruz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


In this paper we present a proposal to analyze market baskets using minimum spanning trees, based on couplings between products. The couplings are the result of a learning process with Boltzmann machines from transactional databases, in which the interaction between the different offers of the market are modeled as a network composed by magnetic dipoles of spins that can be in two states ((formula presented)1 or −1). The results offer a systematic way to explore potential courses of action to determine promotions and offers for the retail manager.

Original languageEnglish
Title of host publicationArtificial Neural Networks and Machine Learning – ICANN 2019
Subtitle of host publicationText and Time Series - 28th International Conference on Artificial Neural Networks, 2019, Proceedings
EditorsIgor V. Tetko, Pavel Karpov, Fabian Theis, Vera Kurková
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783030304898
StatePublished - 2019
Event28th International Conference on Artificial Neural Networks, ICANN 2019 - Munich, Germany
Duration: 17 Sep 201919 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11730 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference28th International Conference on Artificial Neural Networks, ICANN 2019


  • Boltzmann learning
  • Ising model
  • Market basket
  • Minimum spanning tree


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