Veri madenciliği algoritmaları ile birliktelik kurallarının belirlenmesi: Perakende sektöründe bir uygulama
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
İstanbul Ticaret Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Market sepet analizi, müşterilerin tek bir alışverişte satın aldığı ürünler dikkate alınarak, satın alma eğilimlerinin şirket veri tabanlarındaki kayıtlar ile ortaya çıkarılması işlemidir. Bu çalışmada; perakende sektöründe faaliyet gösteren büyük bir hırdavat şirketinin beş buçuk yıllık verileri üzerinde market sepet analizi uygulanarak ilişkili ürün kategorileri belirlenmiştir. Birliktelik kurallarının belirlenmesinde Apriori ve FP-Growth algoritmalarının her ikisi de ayrı ayrı çalıştırılarak bu tip bir veri setindeki kullanışlılıkları kıyaslanmıştır. Ayrıca veri seti; Veri Seti-1 ve Veri Seti-2 olacak şekilde ikiye bölünmüş, böylece ilk veri setinden çıkarılan kuralların doğruluğu, ardışık zamanlı verileri içeren ikinci veri setinden çıkarılan kurallar ile karşılaştırılarak kuralların tutarlılığı tartışılmıştır.
Market basket analysis is the process of extracting purchasing trends from records in company databases, taking into account the products that customers buy in a single trade. Market basket analysis is the process of extracting purchasing trends from records in company databases, taking into account the products that customers buy in a single transaction. In this study, a market basket analysis was conducted on a five-and-a-half year data of a large hardware company operating in the retail sector, and related product categories were identified. In determining the association rules, both the Apriori and FP-Growth algorithms were run separately and their usefulness in such a set of data was compared. In addition, the data set was divided into Data Set-1 and Data Set-2 so that the consistency of the rules was discussed by comparing the correctness of rules extracted from the first data set with rules derived from the second data set containing consecutive timed data.
Market basket analysis is the process of extracting purchasing trends from records in company databases, taking into account the products that customers buy in a single trade. Market basket analysis is the process of extracting purchasing trends from records in company databases, taking into account the products that customers buy in a single transaction. In this study, a market basket analysis was conducted on a five-and-a-half year data of a large hardware company operating in the retail sector, and related product categories were identified. In determining the association rules, both the Apriori and FP-Growth algorithms were run separately and their usefulness in such a set of data was compared. In addition, the data set was divided into Data Set-1 and Data Set-2 so that the consistency of the rules was discussed by comparing the correctness of rules extracted from the first data set with rules derived from the second data set containing consecutive timed data.
Açıklama
Fen Bilimleri Enstitüsü, Endüstri Mühendisliği Ana Bilim Dalı
Anahtar Kelimeler
Endüstri ve Endüstri Mühendisliği, Industrial and Industrial Engineering
