In this paper we show the importance of mining totally ordered sequential rules, and in particular we propose an extension of sequential rules where not only the antecedent precedes the consequent, but their itemsets are labelled with an explicit representation of their relative order. This allows us to provide more precise timely recommendations. Our technique has been applied to a real-world scenario regarding the provision of tailored suggestions for supermarket shopping activities.

Mining Totally Ordered Sequential Rules to Provide Timely Recommendations

Dalla Vecchia, Anna;Marastoni, Niccolo;Migliorini, Sara
;
Oliboni, Barbara;Quintarelli, Elisa
2023-01-01

Abstract

In this paper we show the importance of mining totally ordered sequential rules, and in particular we propose an extension of sequential rules where not only the antecedent precedes the consequent, but their itemsets are labelled with an explicit representation of their relative order. This allows us to provide more precise timely recommendations. Our technique has been applied to a real-world scenario regarding the provision of tailored suggestions for supermarket shopping activities.
2023
978-3-031-42940-8
Sequential Rules
Data mining
Recommendations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1104946
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