Research on Segmenting E-Commerce Customer through an Improved K-Medoids Clustering Algorithm

In view of the shortcomings of traditional clustering algorithms in feature selection and clustering effect, an improved Recency, Frequency, and Money (RFM) model is introduced, and an improved K-medoids algorithm is proposed. Above model and algorithm are employed to segment customers of e-commerce...

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Detalles Bibliográficos
Autores principales: Wu, Zengyuan, Jin, Lingmin, Zhao, Jiali, Jing, Lizheng, Chen, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233613/
https://www.ncbi.nlm.nih.gov/pubmed/35761867
http://dx.doi.org/10.1155/2022/9930613

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233613/
https://www.ncbi.nlm.nih.gov/pubmed/35761867
http://dx.doi.org/10.1155/2022/9930613

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