基于回复支持的关键评论提取方法

当前网络中充斥着大量的虚假评论，准确识别出代表用户真实感受的关键评论成为评论分析领域研究的热点问题。为此，提出一种基于回复支持的关键评论提取方法，该方法从用户对评论的反馈行为出发，重点考量评论点赞和评论回复两个指标，通过计算评论点赞率和回复率获取评论的回复支持情况，仅对回复支持度高的评论进行提取，从而剔除了大量虚假或无用的评论，提升了关键评论提取的准确性。最后，通过与现有主流方法进行实验对比，验证了该方法具有较高的正确率和召回率。

Key Comment Extraction Method Based on Reply Support

Online comment is an effective way for users to express their opinions or suggestions on commodities．Analysis of comments is the basis of developing personalized services and improving the performance of commodities． However，there are a lot of false comments in the network． Accurate identification of the key comments which represent users' real feelings has become a hot issue in the field of comment analysis． A key comment extraction method based on reply support was proposed． The proposed method starts from user's feedback behavior to comments，and focuses on two indicators: like comment and comment reply． By calculating the like comment rate and comment reply rate，the method obtains the comment's reply support，only extracts the comment with high reply support，thus eliminating a large number of false or useless comments，and improves the accuracy of key comment extraction． Finally，through the experimental comparison with the existing mainstream methods，it is verified that the proposed method has a high accuracy and recall rate．