RFM Based Market Segmentation Approach Using Advanced K-means and Agglomerative Clustering: A Comparative Study-Reference-Cited by-同舟云学术

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RFM Based Market Segmentation Approach Using Advanced K-means and Agglomerative Clustering: A Comparative Study

Published:2019-02 Issue: Volume: Page:
ISSN:
Container-title:2019 International Conference on Electrical, Computer and Communication Engineering (ECCE)
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Author:

Shihab Sabbir Hossain,Afroge Shyla,Mishu Sadia Zaman

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8672433/8678913/08679376.pdf?arnumber=8679376

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Comparative Analysis between K-Means and Agglomerative Clustering Techniques in Maritime Skill Certification;Compiler;2024-05-31

2. Retail Industry Analytics: Unraveling Consumer Behavior through RFM Segmentation and Machine Learning;2024 IEEE International Conference on Electro Information Technology (eIT);2024-05-30

3. Comparison of K-Medoids and K-Means Algorithms in Segmenting Customers based on RFM Criteria;E3S Web of Conferences;2024

4. Experimental Analysis on Banking Customer Segmentation using Machine Learning Techniques;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

5. Combination of RFM’s (Recency Frequency Monetary) Method and Agglomerative Ward’s Method for Donors Segmentation;2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE);2023-02-16

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