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Kano model integration with data mining to predict customer satisfaction
Khaled Al Rabaiei
,
Fady Alnajjar
,
Amir Ahmad
Department of Computer Science and Software Engineering
Department of Information System and Security
Research output
:
Contribution to journal
›
Article
›
peer-review
20
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Citations (Scopus)
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Keyphrases
Customer Satisfaction
100%
Model Integration
100%
Kano Model
100%
Products or Services
40%
Higher Education
20%
UAE University
20%
Data Mining Techniques
20%
Pearson Correlation Coefficient
20%
Selected Features
20%
Number of Features
20%
Feature Selection Methods
20%
Questionnaire Data
20%
R2 Value
20%
Regression Tree
20%
Feature Selection Models
20%
Decision Tree Regression
20%
XGBoost Regression
20%
Improve Customer Satisfaction
20%
Computer Science
Data Mining
100%
Customer Satisfaction
100%
Integration Model
100%
Feature Selection
33%
Questionnaire Data
16%
Decision Trees
16%
Regression Tree
16%
Pearson Correlation Coefficient
16%
Extreme Gradient Boosting
16%
Engineering
Model Integration
100%
Customer Satisfaction
100%
Feature Extraction
33%
Pearsons Linear Correlation Coefficient
16%
Selection Method
16%
Psychology
Analysis of Variance
100%
Model Selection
100%
Food Science
Analysis of Variance
100%
Economics, Econometrics and Finance
Pearson Correlation Coefficient
100%