Association rule mining to extract knowledge from online store transactions of a turkish retail company: A case study
Yükleniyor...
Dosyalar
Tarih
2014
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
İstanbul Aydın Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
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.
Açıklama
Anahtar Kelimeler
Association Analysis, Apriori Analysis, Data Mining
Kaynak
International Journal of Electronics Mechanical and Mechatronics Engineering
WoS Q Değeri
Scopus Q Değeri
Cilt
4
Sayı
4
