Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company A Case Study
Yazarlar (3)
Elif Şafak Sivri
Prof. Dr. Mustafa Cem KASAPBAŞI İstanbul Ticaret Üniversitesi, Türkiye
Fettullah Karabiber
| Makale Türü |
Özgün Makale
(Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale)
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| Dergi Adı | INTERNATIONAL JOURNAL OF ELECTRONICS MECHANICAL and MECHATRONICS ENGINEERING | ||
| Dergi ISSN | 2146-0604 | ||
| Dergi Tarandığı Indeksler | EBSCO | ||
| Makale Dili | İngilizce | Basım Tarihi | 05-2015 |
| Cilt / Sayı / Sayfa | 4 / 4 / – | DOI | – |
| Makale Linki | http://www.aydin.edu.tr/ijemme/index.asp?id=41 | ||
| UAK Araştırma Alanları |
Bilgi Güvenliği ve Kriptoloji
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| Özet |
| 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. |
| Anahtar Kelimeler |
