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Exploiting Web Reviews for Generating Customer Service Surveys

机译:利用Web评论来生成客户服务调查

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摘要

Traditional customer satisfaction analysis relies on the work of designing, distributing, collecting and analyzing surveys. Surveys that are designed by humans may be subjective, and it is hard to know what service aspects are the most important for customers. To address this issue, this paper proposes a method of automatically generating service surveys through mining Web reviews. Candidate service aspects are extracted using simple extraction rules. Then we rank candidate service aspects in terms of their weights generated by combining co-occurrence method and linear regression method together. Experimental results demonstrate the effectiveness of the proposed method.
机译:传统的客户满意度分析依赖于设计,分发,收集和分析调查的工作。由人设计的调查可能是主观的,因此很难知道哪些服务方面对客户最重要。为了解决这个问题,本文提出了一种通过挖掘Web评论自动生成服务调查的方法。使用简单的提取规则来提取候选服务方面。然后,我们通过将共现方法和线性回归方法结合在一起,根据候选服务方面的权重对它们进行排序。实验结果证明了该方法的有效性。

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