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     Advance Journal of Food Science and Technology


Rice Products Feature Analyzing on the Base of Online Review Mining

Xixiang Sun, Xiaoqing Song and Xiangdong Liu
Wuhan University of Technology, Wuhan 430070, China
Advance Journal of Food Science and Technology  2015  1:49-53
http://dx.doi.org/10.19026/ajfst.7.1265  |  © The Author(s) 2015
Received: August ‎31, ‎2014  |  Accepted: September ‎20, ‎2014  |  Published: January 05, 2015

Abstract

This study aims to investigate the rice product features using online review mining method. The opinion mining is used to do online review data analyze. High-frequency words were extracted from non-structured online reviews text. Then the rice product features were gotten from the factor analysis on the base of high-frequency words. This provided a new method for product feature analyzing which was based on the data mining of online reviews. The proposed method can be used to compare features of rice products which were in the similar category. It also provided new views for understanding consumer brand knowledge. At the end of this study, the online review of rice products were used to verify the scientificity and rationality of this method.

Keywords:

Data mining, online review, opinion mining, rice products,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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