Unsupervised Anomaly Detection of Retail Stores Using Predictive Analysis Library on SAP HANA XS Advanced

Author:

Oliveira João Pedro,Sousa Rui Dinis

Funder

FCT

Publisher

Elsevier BV

Subject

General Engineering

Reference15 articles.

1. Kempen D van. SAP HANA 2.0: An Introduction. Rheinwerk Verlag GmbH; 2019.

2. Alborghetti F, Kohlbrenner J, Pattanayak A, Schrank D, Sboarina P. SAP HANA XSA: Native Development for SAP HANA. Rheinwerk Verlag GmbH; 2018.

3. Chen J, Sathe S, Aggarwal C, Turaga D. Outlier Detection with Autoencoder Ensembles. 17th SIAM Int. Conf. Data Mining, SDM 2017, 2017, p. 90–8. https://doi.org/10.1137/1.9781611974973.11

4. Low-cost Unsupervised Outlier Detection by Autoencoders with Robust Estimation Yoshinao;Ishii;J Inf Process,2019

5. Agrawal S, Agrawal J. Survey on Anomaly Detection using Data Mining Techniques. 19th Int. Conf. Knowl. Based Intell. Inf. Eng. Syst., vol. 60, Elsevier Masson SAS; 2015, p. 708–13. https://doi.org/10.1016/j.procs.2015.08.220

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3. Data Warehouse, Detection and Transfer of Anomalies in Retail Data;The European Journal of Research and Development;2023-07-28

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