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

Cilt: 4 Sayı: 4 1 Aralık 2014
  • Elif Şafak Sivri
  • Mustafa Cem Kasapbaşı
  • Fettullah Karabiber
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EN

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

Öz

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

Kaynakça

  1. Timor M. ,EZERCE A. , GURSOY
  2. U. T., “Müşteri Profili ve Alişveriş Davranışlarını Belirlemede Kümeleme ve Birliktelik Kuralları Analizi: Perakende sektöründe bir uygulama” , İstanbul Üniversitesi İşletme Fakültesi İşletme İktisadı Enstitüsü Dergisi, February 2011 22 68
  3. R. Agrawal, R. Srikant, Fast algorithms for
  4. mining association rules, in: Proceedings of the 20th International Conference on Very Large Data Bases, 1994, pp. 487–499
  5. J. Singh, H. Ram, Dr. J.S. Sodhi, Improving
  6. Efficiency of Apriori Algorithm Using Transaction Reduction International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013
  7. Cheng-Hsiung Weng, Mining fuzzy
  8. specific rare itemsets for education data, Knowledge-Based Systems, Volume 24, Issue 5, July 2011, Pages 697-708, ISSN 0950-7051, http://dx.doi.org/10.1016/j. knosys.2011.02.010.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

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Yazarlar

Elif Şafak Sivri Bu kişi benim
Istanbul Commerce University, Computer Engineering Department, Istanbul, Turkey

Mustafa Cem Kasapbaşı Bu kişi benim
Istanbul Commerce University, Computer Engineering Department, Istanbul, Turkey

Fettullah Karabiber Bu kişi benim
Yildiz Technical University, Computer Engineering Department, Istanbul, Turkey

Yayımlanma Tarihi

1 Aralık 2014

Gönderilme Tarihi

1 Aralık 2014

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2014 Cilt: 4 Sayı: 4

Kaynak Göster

APA
Şafak Sivri, E., Kasapbaşı, M. C., & Karabiber, F. (2014). Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study. International Journal of Electronics Mechanical and Mechatronics Engineering, 4(4), 861-865. https://izlik.org/JA63UF76SC
AMA
1.Şafak Sivri E, Kasapbaşı MC, Karabiber F. Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study. IJEMME. 2014;4(4):861-865. https://izlik.org/JA63UF76SC
Chicago
Şafak Sivri, Elif, Mustafa Cem Kasapbaşı, ve Fettullah Karabiber. 2014. “Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study”. International Journal of Electronics Mechanical and Mechatronics Engineering 4 (4): 861-65. https://izlik.org/JA63UF76SC.
EndNote
Şafak Sivri E, Kasapbaşı MC, Karabiber F (01 Aralık 2014) Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study. International Journal of Electronics Mechanical and Mechatronics Engineering 4 4 861–865.
IEEE
[1]E. Şafak Sivri, M. C. Kasapbaşı, ve F. Karabiber, “Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study”, IJEMME, c. 4, sy 4, ss. 861–865, Ara. 2014, [çevrimiçi]. Erişim adresi: https://izlik.org/JA63UF76SC
ISNAD
Şafak Sivri, Elif - Kasapbaşı, Mustafa Cem - Karabiber, Fettullah. “Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study”. International Journal of Electronics Mechanical and Mechatronics Engineering 4/4 (01 Aralık 2014): 861-865. https://izlik.org/JA63UF76SC.
JAMA
1.Şafak Sivri E, Kasapbaşı MC, Karabiber F. Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study. IJEMME. 2014;4:861–865.
MLA
Şafak Sivri, Elif, vd. “Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study”. International Journal of Electronics Mechanical and Mechatronics Engineering, c. 4, sy 4, Aralık 2014, ss. 861-5, https://izlik.org/JA63UF76SC.
Vancouver
1.Elif Şafak Sivri, Mustafa Cem Kasapbaşı, Fettullah Karabiber. Association Rule Mining to Extract Knowledge from Online Store Transactions of a Turkish Retail Company: A Case Study. IJEMME [Internet]. 01 Aralık 2014;4(4):861-5. Erişim adresi: https://izlik.org/JA63UF76SC