Research Article
A Customer Satisfaction Degree Evaluation Model Based on Support Vector Machine
@INPROCEEDINGS{10.4108/wkdd.2008.2791, author={Wang Ting and Hua Zhiwu}, title={A Customer Satisfaction Degree Evaluation Model Based on Support Vector Machine}, proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining}, publisher={ACM}, proceedings_a={WKDD}, year={2010}, month={5}, keywords={customer satisfaction degree support vector machine multilevel binary tree classifier evaluation model}, doi={10.4108/wkdd.2008.2791} }- Wang Ting
Hua Zhiwu
Year: 2010
A Customer Satisfaction Degree Evaluation Model Based on Support Vector Machine
WKDD
ACM
DOI: 10.4108/wkdd.2008.2791
Abstract
An efficient classification algorithm is proposed for evaluating the customer satisfaction degree. The algorithm is based on the RBF-Kernel support vector machine and multilevel binary tree classifier. Fuzzy membership function was used to quantify the evaluation indices. The evaluation indices and the SVM algorithm were used to design a customer satisfaction degree evaluation model. The novel evaluation method has higher accuracy in comparison with the traditional fuzzy comprehensive evaluation method and BP evaluation method.
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