Research Article
Research on Clothing Product Reviews Mining Based on the Maximum Entropy
@ARTICLE{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}, journal={EAI Endorsed Transactions on Energy Web}, volume={2}, number={4}, publisher={EAI}, journal_a={EW}, 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
EW
EAI
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%.
Copyright © 2015 P. Feng et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
