Computer Science and Information Technology Vol. 8(1), pp. 1 - 12
DOI: 10.13189/csit.2020.080101
Reprint (PDF) (910Kb)


Decision Support System for Multistore Online Sales Based on Priority Rules and Data Mining


Alessandro Massaro *, Antonio Mustich , Angelo Galiano
Dyrecta Lab s.r.l., IT Research Laboratory, via Vescovo Simplicio, Italy

ABSTRACT

The work is focused on the design and implantation of an intelligent multi store E-commerce platform able to manage the orders and the warehouse stock by mean of priority association rules and data mining algorithms. The proposed Decision Support System (DSS) is structured into two main levels: the first one is related to priority rule definition due to the online product requests according with the availability check in different warehouses of stores, and the second one provides important information about sales prediction thus facilitating stock management and consecutively logistic. Specifically, the prototype platform is able to manage the warehouse products of different stores by means a simultaneous comparison of products available in the different stores linked to the platform, and by means of a scalable end-to-end tree boosting system XGBoost algorithm able to predict online sales. The paper has been developed within the framework of an industry project.

KEYWORDS
Multi E-Commerce, Warehouse Product Management, Data Mining

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Alessandro Massaro , Antonio Mustich , Angelo Galiano , "Decision Support System for Multistore Online Sales Based on Priority Rules and Data Mining," Computer Science and Information Technology, Vol. 8, No. 1, pp. 1 - 12, 2020. DOI: 10.13189/csit.2020.080101.

(b). APA Format:
Alessandro Massaro , Antonio Mustich , Angelo Galiano (2020). Decision Support System for Multistore Online Sales Based on Priority Rules and Data Mining. Computer Science and Information Technology, 8(1), 1 - 12. DOI: 10.13189/csit.2020.080101.