Extracting product features from Chinese product reviews

被引：0
作者：
机构：
[1] School of Management, Tianjin University, Tianjin
来源：
Xi, Y. (xiyahui@hbu.edu.cn) | 2013年 / Academy Publisher卷 / 08期
关键词：
Double propagation; HITS; Normalized pattern relevance; Product feature exaction; Product review mining;
D O I：
10.4304/jmm.8.6.647-654
中图分类号：
学科分类号：
摘要：
With the great development of e-commerce, the number of product reviews grows rapidly on the e-commerce websites. Review mining has recently received a lot of attention, which aims to discover the valuable information from the massive product reviews. Product feature extraction is one of the basic tasks of product review mining. Its effectiveness can influence significantly the performance of subsequent jobs. Double Propagation is a state-of-the-art technique in product feature extraction. In this paper, we apply the Double Propagation to the product feature exaction from Chinese product reviews and adopt some techniques to improve the precision and recall. First, indirect relations and verb product features are introduced to increase the recall. Second, when ranking candidate product features by using HITS, we expand the number of hubs by means of the dependency relation patterns between product features and opinion words to improve the precision. Finally, the Normalized Pattern Relevance is employed to filter the exacted product features. Experiments on diverse real-life datasets show promising results. © 2013 Academy Publisher.
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页码：647 / 654
页数：7
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