Abstract：At present, title and description of goods are rarely considered in the research of online reviews at home and abroad, this makes the mining process blindly and mining results are not high accurate. In this article, the authors use the cluster analysis method, consider the title and description, set up a three-level mining model to analyze the online comments, at the same time, a location-clustering-algorithm is proposed. Experimental results show that the method improves the accuracy of mining and reduces the mining time.
梁昌勇, 王倩倩, 陆文星, 丁勇. 结合商品标题和描述的在线评论特征词选择方法研究[J]. 现代图书情报技术, 2011, 27(5): 49-54.
Liang Changyong, Wang Qianqian, Lu Wenxing, Ding Yong. The Online Comments Signature Words Selection with the Title and Description of Goods. New Technology of Library and Information Service, 2011, 27(5): 49-54.
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