Title: Variable item value-based high utility itemset recommendation using statistical approach

Authors: Abdullah Bokir; V.B. Narasimha

Addresses: Department of CSE, UCE, Osmania University, Hyderabad, India; Hadhramout University, Mukalla, Yemen ' Department of CSE, UCE, Osmania University, Hyderabad, India

Abstract: High utility mining has become an absolute requirement for an efficient corporate management procedure. The challenge persists in identifying the top-out or bottom-out conditions in the context of the available HUM solutions, and it is critical for enterprises to manage adequate inventory to have higher yield outcomes. Taking these aspects into consideration, this paper proposed a comprehensive method named as 'variable item value-based high utility itemset recommendation (VIVHUIR)'. Unlike the contemporary models, which are focusing utility mining by constant utility factor, the proposed model is focusing on variable utility factor to perform utility mining based on profitability for an itemset. In addition, the drift (variability) in utility factor detection methodology is fundamentally based on the average true range for an itemset and the relative strength index (RSI) assessment for analysis, which is unique and novel feature of the proposal. To comprehend the elements influencing profit, the proposed four-layered filtering model depends on quantities, demand, supply, and gain/loss inventory. The experimental research of the model refers to potential solutions that are pragmatic in a real-time situation.

Keywords: high utility mining; dynamic utility; average true range; ATR; relative strength index; RSI; economic order quantity; inventory storage cost.

DOI: 10.1504/IJBIDM.2023.132585

International Journal of Business Intelligence and Data Mining, 2023 Vol.23 No.2, pp.101 - 124

Received: 21 Oct 2021
Accepted: 23 Feb 2022
Published online: 30 Jul 2023 *

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