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New Technology of Library and Information Service  2013, Vol. Issue (12): 70-73    DOI: 10.11925/infotech.1003-3513.2013.12.11
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Research on the Method of Extracting Features from Chinese Product Reviews on the Internet
Wang Yong, Zhang Qin, Yang Xiaojie
School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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Abstract  Aim for better solving the problem of extracting features from Chinese product reviews on the Internet, an approach using FP-growth algorithm is proposed to obtain the set of candidate product features. Then, the candidate product features are filtered according to the rules of p-support, non-features frequent nouns and PMI threshold filtering technology. Finally, the final product features set are obtained. Thus, the automatic mining of product features information from Chinese customer reviews on the Internet is achieved. The proposed method is tested with the cell phone reviews from Datatang and the results show that the presented method is valid and effective.
Key wordsProduct features      Features extracting      Association rules      Review mining     
Received: 12 August 2013      Published: 08 January 2014
:  TP393  

Cite this article:

Wang Yong, Zhang Qin, Yang Xiaojie. Research on the Method of Extracting Features from Chinese Product Reviews on the Internet. New Technology of Library and Information Service, 2013, (12): 70-73.

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