【摘要】 随着电子商务的迅速发展,在互联网上涌现了大量评价快递服务的用户评论,这些评论信息对于快递服务企业具有重要的价值。通过文本挖掘算法对用户评论进行处理,可以挖掘出快递服务的主要特征,并有望利用这些特征构建一套快递服务质量评价体系。文章对快递服务特征挖掘进行了深入的研究,首先,提出了一种基于语义分析的快递服务特征提取算法,实现了对用户评论的特征挖掘;其次,采用从亚马逊评论数据集中获得的评论语料,对该算法进行了数据实验;最后,使用查准率和查全率来进行算法的性能评估,实验结果证明了算法的有效性。更多还原

【Abstract】 With the rapid development of e-commerce, on the internet, a large number of user reviews with regard to express service have sprung up. To express service enterprises, these comments are of great value. Through the text mining algorithm, we can excavate the main features of the express service from user reviews, and build a set of express service quality evaluation system based on these characteristics hopefully. This paper made an in-depth study of the mining of express service features.In the first place, a feature extraction algorithm of express service based on semantic analysis was proposed to realize the feature mining of user reviews. In the second place, reviews corpus from Amazon review dataset was used to make data experiment. In the end, we used precision rate and recall rate to evaluate the performance of the algorithm, and the experimental results demonstrated the effectiveness of the algorithm.更多还原