摘要
近年来,消费多样化刺激越来越多的外国产品进入国内市场,但质量安全形势越发严峻。现今,越来越多的政府和网络新闻媒体将新闻动态实时发布到其官方网站上,网络新闻整合了各政府部门以及媒体舆论的质量监管信息。文中基于Python数据挖掘研究方法进行新闻文本分析,结合网页布局原则,选择进口服装为研究对象,爬取进口服装质量新闻文本,同时构建语义词典,应用该词典和新闻数据对进口服装质量情况进行分析。质量词典的建立有利于质量新闻的大数据分析,对整合、综合多头质量监管、质量治理信息,做出有益的尝试,应用词典对进口商品质量分析的结果,也能为相关部门及时划定重点监控地区和重点监控产品提供决策支持。
In recent years,consumption diversification has stimulated more and more foreign products to enter the domestic market,while the quality and safety situation has become more severe.Nowadays,more and more government and online news medias publish news trends on their official websites in real time,and online news integrates quality supervision information of various government departments and medias.This paper analyzes news text based on the Python data mining research method,combines web page layout principles,selects imported clothing as the research object,crawls news text about imported clothing quality,and constructs a semantic dictionary,through witch,as well as news data,to analyze the quality of imported clothing.The establishment of the quality dictionary is conducive to the big data analysis of quality news,and it has made a useful attempt to comprehensively integrate multi-head quality supervision and quality management information.The application of the results of the dictionary's quality analysis of imported goods can also provide decision support for relevant departments to timely define key monitoring areas and key monitoring products.
作者
郭宝琳
GUO Bao-Lin(School of Economics and Trade,Guangdong University of Technology,Guangzhou 510520,Guangdong,China)
出处
《质量技术监督研究》
2020年第5期49-52,共4页
Quality and Technical Supervision Research
