Market Basket Analysis Using Boltzmann Machines
- Mauricio A. Valle(corresponding author),
- Gonzalo A. Ruz
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Research
Peer-reviewPublication Information
Output type
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Research
Peer-reviewHost publication Subtitle
Text and Time Series - 28th International Conference on Artificial Neural Networks, 2019, ProceedingsOriginal language
EnglishPages from-to (Number of pages)
Pages 611-623 (13 pages)Publication milestones
- Published - 01/01/2019
Publication status
Published - 01/01/2019
Publisher
Springer VerlagPublication 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)
9783030304898Publication IDs
- Scopus: 85072868525
Host publication title
Artificial Neural Networks and Machine Learning – ICANN 2019Host 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.
Publication metrics
Metrics
SciVal
FWCI
0.26
PlumX, opens in new tab
Captures
4
Citation count
2