Systematic Review of Machine Learning Methods in Customer Satisfaction Prediction-Reference-Cited by-同舟云学术

Systematic Review of Machine Learning Methods in Customer Satisfaction Prediction

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:2022 10th International Conference on Orange Technology (ICOT)
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Author:

Xiao Guohua¹,Kuan Ta-Wen¹,Li Fengying²,Ling Mingsheng³,Tseng Shih-Pang¹

Affiliation:

1. School of Information Science and Technology, Sanda University,Shanghai,China

2. Lifelong Education College, Shanghai Jiaotong University,Shanghai,China

3. School of Software and Big Data, Changzhou College of Information Technology,Changzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10008107/10008108/10008132.pdf?arnumber=10008132

Reference14 articles.

1. XGBoost

2. A XGBoost Method Based on Telecom Customer Satisfaction Enhancement Strategy

3. Determination of Customer Satisfaction using Improved K-means algorithm

4. Prediction of customer satisfaction using naive bayes, multiclass classifier, k-star and ibk;roy;4th International Workshop on Soft Computing Applications,2016

5. Can machine learning techniques predict customer dissatisfaction? A feasibility study for the automotive industry

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