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Market Basket Analysis Using Boltzmann Machines

  • Mauricio A. Valle(corresponding author)
    ,
  • Gonzalo A. Ruz
*Corresponding author for this work
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Host publication Subtitle

Text and Time Series - 28th International Conference on Artificial Neural Networks, 2019, Proceedings

Original language

English

Pages from-to (Number of pages)

Pages 611-623 (13 pages)

Publication milestones

  • Published - 01/01/2019

Publication status

Published - 01/01/2019

Publisher

Springer Verlag

Publication series

  • Publication series name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    ISSN (Print): 0302-9743
    ISSN (Electronic): 1611-3349
    Volume: 11730 LNCS

ISBN (Print)

9783030304898

Publication IDs

  • Scopus: 85072868525

Host publication title

Artificial Neural Networks and Machine Learning – ICANN 2019

Host publication editors

  • Igor V. Tetko
  • Pavel Karpov
  • Fabian Theis
  • Vera Kurková

Abstract

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.

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Scopus
citations
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0.26

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4
Citation count
2