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作 者:何媛 陈亮[1] 李丰妤 张志远 HE Yuan;CHEN Liang;LI Feng-yu;ZHANG Zhi-yuan(South China University of Technology,Guangzhou 510006,China)
机构地区:[1]华南理工大学,广州510006
出 处:《包装工程》2020年第10期228-234,共7页Packaging Engineering
摘 要:目的针对数以万计的电子商务交易量背后产生的海量评价数据,给用户带来的信息过载、检索低效等问题,探索合理的可视化方案,辅助用户进行购买决策,帮助商家提取有效反馈以帮助产品优化。方法以京东平台商品的评论数据为例,提出一种电子商务用户反馈文本可视化方法,以口红为目标商品,采用网络爬虫技术从电商平台抓取用户评论文本数据并进行整理分析,针对文本数据采取自然语言处理技术进行语义分析并归类,得出可直接用于可视化的文本数据,进一步提取了口红色号、价格趋势、关注词频率三个评论数据种类,价格对比、口红色号可视化等用户指标,借助Tableau可视化工具对数据进行映射,建立了趋势图和分布图,得到直观的可视化图表,为用户提供了更美观且具有交互功能的信息浏览方式。结论所提出的可视化方案采用视觉认知的方式提取关键信息,能有效降低用户浏览文本信息的时间成本,此方案的评估结果也获得了较高的评分,对推进电商平台数据可视化具有一定指导意义。The work aims to explore reasonable visualization schemes to assist users in making purchasing decisions and help merchants extract effective feedback for product optimization, with respect to such problems as overloaded information and inefficient retrieval brought to users by huge amounts of evaluation data generated by tens of millions of e-commerce transactions. With the comment data of the products of Jingdong platform as an example, a method for visualizing the feedback text of e-commerce users was proposed. Taking the lipstick products as the target goods, the web crawler technology was used to capture the user’s comment text data from the e-commerce platform for their analysis. The text data were semantically analyzed and classified by natural language processing technology, and the text data directly used for visualization were obtained. Three kinds of comment data(lipstick color code, price trend and frequency of attention word), price comparison, lipstick color code visualization and other user indicator were extracted. Tableau visualization tools were used to map data, create trend and distribution maps, and get intuitive visual charts to provide users with more beautiful and interactive information browsing. The proposed visualization scheme can extract key information and effectively reduce the time cost for users to browse text information by means of visual cognition. The evaluation result of this scheme also obtains a high score. The proposed scheme has certain guiding significance for advancing the data visualization of e-commerce platforms.
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