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.
王永, 张勤, 杨晓洁. 中文网络评论中产品特征提取方法研究[J]. 现代图书情报技术, 2013, (12): 70-73.
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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