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Improving retail sales through unsupervised collective-contextual anomaly detection: a deep reconstruction autoencoder for network-wide sales analysis

Crossref DOI link: https://doi.org/10.1007/s10489-025-06749-y

Published Online: 2025-07-05

Published Print: 2025-08

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Fonseka, Tehara

Tulenkov, Anton

Grolinger, Katarina https://orcid.org/0000-0003-0062-8212
Funding

Funding for this research was provided by:

NSERC (RGPIN-2018-06222)

Mitacs (Mitacs Internship Grant)
License Information

Text and Data Mining valid from 2025-07-05

Version of Record valid from 2025-07-05
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Article History

Accepted: 21 June 2025

First Online: 5 July 2025

Declarations

:

: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Katarina Grolinger reports financial support was provided by Natural Sciences and Engineering Research Council of Canada. Tehara Fonseka reports financial support was provided by Mitacs Canada.

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