Re-mining item associations: Methodology and a case study in apparel retailing
Yükleniyor...
Dosyalar
Tarih
2011-12
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.
Açıklama
This work is financially supported by the Turkish Scientific Research Council under Grant TUBITAK 107M257. The authors would also like to thank one anonymous reviewer for helpful comments.
Anahtar Kelimeler
Data mining, Association mining, Negative association, Apparel retailing, Inductive decision trees, Retail data, Rules, Complexity, Framework, Algorithm, Decision trees, Parallel processing systems, Trees (mathematics)
Kaynak
Decision Support Systems
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
52
Sayı
1
Künye
Demiriz, A., Ertek, G., Atan, S. T. & Kula, U. (2011). Re-mining item associations: Methodology and a case study in apparel retailing. Decision Support Systems, 52(1), 284-293. doi:10.1016/j.dss.2011.08.004
