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Authors: Manuel Sánchez-Laguardia ; Gastón García González ; Emilio Martinez ; Sergio Martinez ; Alicia Fernández and Gabriel Gómez

Affiliation: Facultad de Ingeniería, Universidad de la República, Uruguay

Keyword(s): Sparse Time Series, GAN, VAE, Data Augmentation.

Abstract: In recent years, there has been significant growth in the application of deep learning methods for classification, anomaly detection, and forecasting of time series. However, only some studies address problems involving sparse or intermittent demand time series, since the availability of sparse databases is scarce. This work compares the performance of three data augmentation approaches based on generative models and provides the code used to generate synthetic sparse and non-sparse time series. The experiments are carried out using a newly created sparse time series database, ASTELCO, which is generated from real e-commerce data (STELCO) supplied by a mobile Internet Service Provider. For the sake of reproducibility and as an additional contribution to the community, we make both the STELCO and ASTELCO datasets publicly available, and openly release the implemented code.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Sánchez-Laguardia, M., García González, G., Martinez, E., Martinez, S., Fernández, A. and Gómez, G. (2025). ASTELCO: An Augmented Sparse Time Series Dataset with Generative Models. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-730-6; ISSN 2184-4313, SciTePress, pages 283-290. DOI: 10.5220/0013185900003905

@conference{icpram25,
author={Manuel Sánchez{-}Laguardia and Gastón {García González} and Emilio Martinez and Sergio Martinez and Alicia Fernández and Gabriel Gómez},
title={ASTELCO: An Augmented Sparse Time Series Dataset with Generative Models},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2025},
pages={283-290},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013185900003905},
isbn={978-989-758-730-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - ASTELCO: An Augmented Sparse Time Series Dataset with Generative Models
SN - 978-989-758-730-6
IS - 2184-4313
AU - Sánchez-Laguardia, M.
AU - García González, G.
AU - Martinez, E.
AU - Martinez, S.
AU - Fernández, A.
AU - Gómez, G.
PY - 2025
SP - 283
EP - 290
DO - 10.5220/0013185900003905
PB - SciTePress

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