Customer Segmentation using Machine learning Techniques
Author:
Affiliation:
1. NED University of Engineering and Technology,Dept. of Computer Science and I.T,Karachi,Pakistan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10073965/10075101/10075194.pdf?arnumber=10075194
Reference17 articles.
1. Comparative Unsupervised Clustering Approaches for Customer Segmentation
2. Research on Segmenting E-Commerce Customer through an Improved K-Medoids Clustering Algorithm
3. Hybrid soft computing approach based on clustering, rule mining, and decision tree analysis for customer segmentation problem: Real case of customer-centric industries
4. Prediction of Consumer Behaviour using Random Forest Algorithm
5. K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data
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1. An Elegant Evaluation: Triangulating Clustering Methods for Customer Segmentation;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22
2. Segmentation of E-Commerce Data Using K-Means Clustering Algorithm;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01
3. Predicting Customer Satisfaction in Brazil E-commerce: A Comparative Study of Machine Learning Techniques;2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2023-11-03
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