Evaluating market basket data with formal concept analysis

Alp Üstündağ, Mert Bal*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümBölümbilirkişi

1 Atıf (Scopus)

Özet

Knowledge discovery process from databases has gained importance recently. Finding and using the valuable and meaningful data which is hidden in large databases can have strategic importance for the organizations to gain competitive advantage. In this context, data mining methods are used to analyze customer purchasing data which is called “market basket analysis”. This analysis provides insight into the combination of products within a customer’s ‘basket’. In this study, a market basket analysis is conducted to identify a customer purchasing behaviour with Formal Concept Analysis (FCA). The FCA technique is one of the data mining methods using formal contexts and concept lattices. So, this method provides to create association rules based on lattices reflecting the relationships among the attributes in a database.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıSpringer Proceedings in Complexity
YayınlayanSpringer
Sayfalar113-118
Sayfa sayısı6
DOI'lar
Yayın durumuYayınlandı - 2014

Yayın serisi

AdıSpringer Proceedings in Complexity
ISSN (Basılı)2213-8684
ISSN (Elektronik)2213-8692

Bibliyografik not

Publisher Copyright:
© Springer Science+Business Media Dordrecht 2014.

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