2024
DOI: 10.22624/aims/cisdi/v15n2p2
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FePARM: The Frequency-Patterned Associative Rule Mining Framework on Consumer Purchasing-Pattern for Online Shops

Bridget Ogheneovo Malasowe,
Ejaita Abugor Okpako,
, Nwanze Chukwudi Ashioba
et al.

Abstract: Transaction data often is a true presentation of consumers’ buying behavior, stored as a set of relational records, which properly harnessed via mining – can help businesses improve their sales volume as a decision support system. Managing such a system can pose many issues to biz such as feature evolution, concept evolution, concept drift, and infinite data length – and often makes it impractical to effectively store such big-data. To curb this, previous studies have assumed data to be stationary in using ass… Show more

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