Research On Intelligent Classification And Visualization Of Complaint Information Of Vehicle Quality Network

In recent years,the Internet industry has developed rapidly with the progress of human society.The amount of social data continues to accumulate,showing explosive growth.The era of big data has quietly arrived.At the same time,as an important channel for automobile consumers to complain when they encounter quality problems,online complaints have spawned a large number of automobile quality complaint websites.The automobile quality complaint information contained in these websites provides researchers with a large amount of data.Therefore,this paper takes the car quality website as the research object,uses the network data collection technology and text classification technology to collect and classify the car quality website complaint data,and designs a visual platform to display the data analysis results.The specific research work is as follows:To solve the problem of weak scalability of ordinary crawlers and anti crawler measures for websites,we first use the Scrapy framework to solve the problem of weak scalability of ordinary crawlers;Secondly,when collecting historical data,we broke through the website’s anti crawler measures by setting the crawler frequency,simulating the request header,and dynamic IP;Finally,the data collected in this paper are presented.As it is difficult to classify the collected data manually,the deep learning method is used to classify the data.First,the collected data is preprocessed to eliminate the dirty data in the data,and a data set of vehicle quality complaints is made;Secondly,the text classification network Text CNN is improved,and the CAM attention mechanism is introduced to make up for the problem of information loss caused by the maximum pooling of the original network.At the same time,through learning the relevant parameters between channels,the corresponding weights are generated for the feature channels to obtain deeper semantic information.The experimental results show that the method can effectively improve the text classification effect on the public dataset and the self-made dataset in this paper;Finally,the model is used to expand the data set of vehicle quality complaints and information mining.In order to better show the effect of complaint data analysis,this paper designs a visual platform that integrates collection,classification and analysis.It uses the Django framework to complete the back-end design of the platform and the Bootstrap framework to complete the front-end design of the platform.Finally,the platform was successfully implemented,and combined with various charts,the overall distribution of complaints,complaint time of each complaint category,keywords of each complaint category,new car complaints and other information were displayed intuitively.Based on the use of the vehicle quality complaint data visualization platform of the Vehicle Quality Network,it will contribute to the risk control,supervision and management of China’s automobile quality and safety problems.Figure [59] Table [13] Reference [87]...