Research Article
Research on Clothing Product Reviews Mining Based on the Maximum Entropy
@INPROCEEDINGS{10.4108/eai.19-8-2015.2260919, author={Pengfei Feng and Qinghong Yang}, title={Research on Clothing Product Reviews Mining Based on the Maximum Entropy}, proceedings={11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness}, publisher={EAI}, proceedings_a={QSHINE}, year={2015}, month={8}, keywords={association rules; the maximum entropy; review classification}, doi={10.4108/eai.19-8-2015.2260919} }- Pengfei Feng
Qinghong Yang
Year: 2015
Research on Clothing Product Reviews Mining Based on the Maximum Entropy
QSHINE
IEEE
DOI: 10.4108/eai.19-8-2015.2260919
Abstract
this paper excavated the review theme of clothing products by method of association rules, and built a maximum entropy model for the reviews classification. Then this paper did experimental verification to large-scale clothing product reviews classification, which verified the practical effect that maximum entropy model had in the comment text classification problems. In the process of classification, the maximum entropy model had a good effect, of which accuracy was over 90%.
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