Türk Perakende Şirketindeki Çevirimiçi Alış Verişler için İlişkililik Kurallarını Çıkarılması: Durum Çalışması

Year 2019, , 1176 - 1186, 31.07.2019

Elif Şafak Sivri Mustafa Cem Kasapbaşı

https://doi.org/10.29130/dubited.510529

Abstract

Extracting Association Rules of Turkish Retail Company from Online Transactions: Case Study

Abstract

The extracting association
rules of inter-user-product relations used by companies in decision-making
processes have been popular for some time, especially for market basket
analysis. In this study it is aimed to discover association rules from original
online store transaction of a Turkish retail company, in order to help
administrator and decision maker also Customer Relationship Management
department to initiate campaigns. The main objective is to find out which product
item sets are bought together. In order to better compare the results the data
are analyzed with and without clustering according to range of ages and gender.
Data mining Association analysis methods such as Apriori Algorithm, FP-Growth
(Frequent Pattern) then applied which are used to extract association rules.
Moreover some of the collaborative filtering metrics namely Jaccard, Pearson,
and Cosine function are used to understand the association between products to
obtain a recommendation system. The proposed recommendation methods
successfully recommended the associated product for the obtained original
dataset as high as %65 accuracy. Obtained association rules are shared with the
marketing department to initiate and direct forthcoming marketing campaigns.

Keywords

Data mining, Associative analysis, apriori algorithm, FP-Growth, e-commerce

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