Matrix and Tensor factorization for Customer behavior analysis

Matrix and Tensor factorization for Customer behavior analysis

In this paper, we present a system to analyze consumer be- havior and cluster the customers accordingly. It is based on matrix and tensor factorization techniques and k-means clus- tering algorithm. Factorizing the matrix that contains cus- tomers and the items they purchased, we get a relatively low dimensional latent factors for users. Then this factors are used to cluster the customers. We used this system on the Obase data set that contains past sales data and customer demographics for a major retail store.

Project Poster: 

Project Members: 

Cem Özen

Project Advisor: 

Ali Taylan Cemgil

Project Status: 

Project Year: 

2015
  • Fall

Bize Ulaşın

Bilgisayar Mühendisliği Bölümü, Boğaziçi Üniversitesi,
34342 Bebek, İstanbul, Türkiye

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