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Market Basket Analysis on Retail Stores of Electronic Devices
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2018) Topçu, Feray Ece; Kırbız, Serap
Market basket analysis is a technique that discovers the relationship between the pairs of products purchased together. It simply analyses the purchase coincidence with the products purchased among the sales transactions and explain what is purchased with what. This study presents a market basket analysis to discover the association rules between products within a dataset that is extracted from one of a leading retail company of electronic devices. The aim is to understand the purchasing behavior trends by examining which products are purchased together. The Apriori algorithm provides the opportunity to discover association rules. Market basket analysis is developed with R Language. R community has a library for association rules that’s called “arules”. Additionally, “arulesViz” and “plotly” libraries are used to visualize the output of analysis. Further steps to this study could be diversification of stores groups through machine learning algorithms and according to this classification, market basket analysis may apply on generated classes of the stores separately. In addition, the output of market basket analysis can be input for a recommendation engine.

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