Elif Şafak Sivri, Mustafa Cem KASAPBAŞI, Fettullah Karabiber

Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study

Data mining techniques have been implemented in many fields namely, marketing, insurance, finance, medicine, computer science and many more. In marketing it is used as a tool to cluster and classify customers so that their buying patterns, demographical information, market basket can be analyzed to help the CRM representative and decision makers [1]. In this study online store transactions of multi-branch Turkish Retail Company have been analyzed and many associations rules have been discovered. The analyzed volume of transactions of completed sales exceeds 14000 for a single season. At first data is cleaned from unrelated fields then presented to R studio to implement the Apriori algorithm[2] in order to extract knowledge and obtain association rules between goods. Results are proven be worthy over the conventional methodologies. The extracted data are tested successfully with a sample group of customers to validate the association rules which give unique insights about customer behaviors.

Keywords:

Association analysis, Apriori Analysis, Data Mining,

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International Journal of Electronics Mechanical and Mechatronics Engineering-Cover

ISSN: 2146-0604
Başlangıç: 2011
Yayıncı: İstanbul Aydın Üniversitesi

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Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study

Elif Şafak Sivri, Mustafa Cem KASAPBAŞI, Fettullah Karabiber