Open Access

ARTICLE

A Survey on Methods and Applications of Intelligent Market Basket Analysis Based on Association Rule

Monerah M. Alawadh^*, Ahmed M. Barnawi

King Abdulaziz University, Jeddah, 21589, The Kingdome of Saudi Arabia

* Corresponding Author: Monerah M. Alawadh. Email:

Journal on Big Data 2022, 4(1), 1-25. https://doi.org/10.32604/jbd.2022.021744

Received 18 October 2021; Accepted 23 November 2021; Issue published 04 May 2022

Abstract

The market trends rapidly changed over the last two decades. The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques. Market Basket Analysis has a tangible effect in facilitating current change in the market. Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications. MBA initially uses Association Rule Learning (ARL) as a mean for realization. ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’ behavior. An important motive of using such techniques is maximizing the business profit as well as matching the exact customer needs as closely as possible. In this survey paper, we discussed several applications and methods of MBA based on ARL. Also, we reviewed some association rule learning measurements including trust, lift, leverage, and others. Furthermore, we discuss some open issues and future topics in the area of market basket analysis and association rule learning.

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Keywords

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