Elektronik ticaret müşteri segmentasyonu yumuşak kümeleme yaklaşımlarının performans analizi

Öz

Denetimsiz makine öğrenmesinin en önemli araştırma alanlarından biri olan yumuşak kümeleme, gerçek yaşam uygulamaları için daha uygun sonuçlar sağlaması nedeniyle tercih edilmektedir. Kavramın temel fikri, bir öğenin birden fazla kümeye ait olabilmesidir. Analiz için genellikle bulanık tabanlı yaklaşımlar uygulanmaktadır. Özellikle veri yetersizliği nedeniyle yumuşak kümeleme algoritmaları düşük performans göstermektedir. Bu çalışmada, Gri Sistem Teorisine dayalı yeni bir yumuşak kümeleme yöntemi geliştirilmiştir. Yöntem ve literatürde kullanılan diğer yumuşak kümeleme yaklaşımları, bir e-ticaret şirketine ait müşteri işlem verilerini içeren veri setine müşteri segmentasyonu için uygulanmıştır. Sonuçlara göre geliştirilen yöntemin diğer yumuşak kümeleme algoritmalarına kıyasla küçük veri setlerinde başarılı sonuçlar verdiği belirlenmiştir.

Anahtar Kelimeler

• Yumuşak kümeleme
• Örtüşen kümeleme
• Gri sistem teorisi
• Yumuşak gri ilişkisel kümeleme
• Müşteri segmentasyonu

Performance analysis of soft clustering approaches for e-commerce customer segmentation

Abstract

Soft clustering, which is one of the most important research areas of unsupervised machine learning, is preferred because it provides more suitable results for real-life applications. The fundamental idea of concept is that an item can belong to multiple clusters. Fuzzy-based approaches are generally applied for analysis. Especially due to the insufficient data, soft clustering algorithms have poor performance. In this study, a new soft clustering method based on Grey System Theory has been developed. The method and other soft clustering approaches used in the literature were applied for customer segmentation to a dataset containing customer transaction data of an e-commerce company. According to the results, it was determined that the developed method has given more successful results in small datasets compared to other soft clustering algorithms.

Keywords

• Soft clustering
• Overlapping clustering
• Grey system theory
• Soft grey relational clustering
• Customer segmentation

Kaynakça

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