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目的基于大数据环境,应用热点挖掘系统结构模型,对网上药店在线评论的影响因素进行研究。方法首先运用ICTCLAS和AntConc等工具提取评论文本中的热点词,其次描述规范化的数据表示形式,最后通过Chameleon聚类算法实现热点评论的聚类和话题抽取,并对识别得到的热点评论进行分析。结果通过对识别得到的热点评论进行分析,得到了影响网上药店在线评论的主要因素,并通过层次分析法和问卷调研法,计算得到网上药店在线评论影响因素的排名顺序。结论消费者在网上药店消费过程中更加关注网上药店经营的规范性、商品物流配送和与医保衔接的问题,可以为网上药店提高消费者信任和药品销售量提供决策依据。
Objective To study the influencing factors of online reviews of online pharmacies based on big data environment and application hotspot mining system structure model. Firstly, hot keywords in review texts were extracted by tools such as ICTCLAS and AntConc. Secondly, the normalized data representation was described. Finally, the clustering and topic extraction of hot comment were realized by using Chameleon clustering algorithm, and the hot comment comments were analyzed. Results The main influencing factors of the online pharmacies online pharmacies were analyzed by analyzing the hot comment identifications. The order of influencing factors of the online pharmacy online reviews was calculated by using the analytic hierarchy process and the questionnaire survey method. Conclusions Consumers pay more attention to the normative operation of online pharmacies, the distribution of goods and the connection with medical insurance during the process of online pharmacy consumption, which can provide decision-making basis for online pharmacies to enhance consumer trust and drug sales volume.