基于数据挖掘的动车组乘客需求动态获取方法研究

Research on Dynamic Elicitation Method of Subway Passenger requirement Based on Data Mining

目前动车组制造商主要关注运营商需求而较少关注乘客需求,这影响乘客对动车组的满意程度,不利于提高企业的市场竞争力。此外现有的研究对运营商需求分析较多,而对终端用户乘客需求分析较少。提出了一种基于数据挖掘的动车组乘客需求动态获取方法。首先,基于需求词库从社交网络平台中获取用户发文数据;其次,基于规则及朴素贝叶斯分类进行文本去噪处理;最后,基于K-means的主题聚类获取乘客需求项及其偏好。以微博挖掘为例,获取动车组乘客需求,验证了该方法的有效性和可行性。

At present,EMU manufacturers mainly focus on the needs of operators and pay less attention to passenger requirement,which affects passengers’satisfaction with EMUs,which is not conducive to improving the market competitiveness of manufacturers.In addition,most existing research analysis on the needs of operators,but less on the requirement of end-user passengers.Therefore,this paper proposes a method for dynamic acquisition of passenger requirement based on data mining.Firstly,obtaining user-opinion data from the social network platform,which based on the requirement dictionary;secondly,denoising data based on rules and Naive Bayes classification;finally,based on K-means-based topic clustering to obtain passenger requirement items and their preferences,taking Weibo mining as an example to obtain EMU passenger requirement,the validity and feasibility of the method are verified.