质量安全网络信息分类系统的设计与实现

发布时间：2019-03-13 10:51

【摘要】：近年来，我国频繁爆出重大的产品质量安全问题，这些问题不仅已经严重影响消费者的身心健康，甚至会影响社会安定和我国经济的长远发展。传统的质量安全监测手段主要是通过产品抽样检测、调查问卷、消费者投诉等方式完成，存在效率低下，覆盖面窄等缺点，难以应对这一日益严重的难题。随着互联网的发展，网络已经成为人们表达观点和发表言论的重要途径，这其中也包含消费者对产品质量的反馈信息，通过对这些反馈信息进行采集和分析，对质量安全问题的监测和预警有巨大的价值。本文设计并实现了一个分类系统，该系统利用文本分类技术对互联网上的质量安全信息进行自动处理，该系统主要功能包括：1）行业分类。采用支持向量机算法实现文本多分类器对质量安全信息按照所属行业进行分类，从而更好地对数据进行组织，便于对数据进行管理和查找。2）信息过滤。采用朴素贝叶斯算法实现文本二分类器对质量安全信息进行过滤，将无关的数据过滤，对数据进行提纯，为用户提供准确的质量安全数据。3）风险分类。采用支持向量机算法实现文本多分类器对各个行业的数据进行风险分类，，将质量信息细化到具体的风险类别，便于对产品风险进行监测和预警。本文设计开发的文本分类系统经过测试分析表明，该系统能够对质量安全网络信息进行有效的处理，并对其他领域的文本分类系统有借鉴意义。
[Abstract]:In recent years, great problems of product quality and safety have appeared frequently in our country. These problems not only seriously affect the physical and mental health of consumers, but also affect the social stability and the long-term development of our economy. The traditional means of quality and safety monitoring are mainly through product sampling, questionnaire, consumer complaints and other ways, there are low efficiency, narrow coverage and other shortcomings, it is difficult to deal with this increasingly serious problem. With the development of the Internet, the network has become an important way for people to express their views and express their opinions, which also includes the feedback of consumers on the quality of products, and through the collection and analysis of these feedback information, Monitoring and early warning of quality and safety problems are of great value. This paper designs and implements a classification system, which uses text classification technology to automatically process the quality and safety information on the Internet. The main functions of the system are as follows: 1) Industry classification. Support vector machine (SVM) algorithm is used to classify the quality and safety information according to their industries, so as to better organize the data and facilitate the management and search of the data. 2) Information filtering. The naive Bayesian algorithm is used to filter the quality and safety information by the text two classifier. The independent data is filtered and the data is purified to provide users with accurate quality and safety data. 3) risk classification. Using the support vector machine (SVM) algorithm, the text classifier is used to classify the data of various industries, and the quality information is refined to the specific risk category, which is convenient for monitoring and early warning of product risk. The text classification system designed and developed in this paper has been tested and analyzed, which shows that the system can deal with the quality and safety network information effectively, and can be used for reference in other fields of text classification system.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.08

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