To help sellers timely and effectively get the commodity reviews, the author proposed a commodity review detection method based on the key word extraction. Based on the Chinese word segmentation, this method firstly extracted the candidate keywords based on part of speech tagging, and then filtered out noises based on the rules. The paper extracted the dynamic co-occurrence of the commodity reviews, and extended the keywords based on these dynamic co-occurrences. Finally the commodity review detection method based on the keyword was realized. The experimental results show that, compared to the basic model, the proposed method can increase the F-Measure by 34.8%, which proves that efficient key word extraction is very useful to the commodity review detection.%为及时有效地获取商品评价信息,提出了基于评价对象识别的商品评价信息检测方法.首先在中文分词的基础上,依据词性标注结果抽取商品评价信息中的候选评价对象；然后基于规则过滤和共现扩展的方法得到精准评价对象；最后实现了基于评价对象识别的商品评价信息检测方法.实验结果表明,与基本模型相比,提出的商品评价信息检测方法的F-Measure提高了34.8％,证明了充分挖掘商品评价信息中的评价对象可以非常有效地改善检测方法的性能.
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