Network Recruitment Information Mining And Analysis Based On Association Rules

At present,there are various types of websites and APPs for companies to recruit and job seekers to find jobs,and these various types of recruitment websites also bring tens of thousands of recruitment information.In order to make full use of these recruitment data and dig deep into its potential value,this paper uses data mining technology to mine and analyze the recruitment data the website of Zhilian,and designs a visualization system to display the data analysis results.The main research contents and results are as follows:(1)Aiming at the real-time and richness of the online recruitment data set,this article used web crawler technology to obtain Internet industry data from the Zhaopin website.It deleted,converted and cleaned the obtained data set to ensure data quality.(2)A DTH-Apriori algorithm(dataset compress,transaction compress and hash technology on apriori)was proposed,which combined data set compression,transaction compression and hash technology.The traditional Apriori algorithm,the FPgrowth algorithm and the optimized Apriori algorithm were used to analyze the correlation degree of the attributes such as salary and academic requirements of Internet-related positions.The experimental results not only verify the strong association rules between the position factors,but also show that the optimization algorithm speed has a certain increase and it is not easily affected by the minimum support.(3)Aiming at the guiding role of popular positions and skills on enterprises and universities,this article analyzed the recruitment positions and career requirements in the data set to obtain five popular positions(Java,Web front-end,algorithm,big data and PHP)in the Internet industry and key words of their skills.Then it provided suggestions for job seekers.(4)In order to better display the effect about data analysis of online recruitment,this paper designs a data analysis system of recruitment that integrates crawling of recruited data,query,analysis and visualization of analysis results.First,based on functional requirements,design the overall architecture of the system according to the data layer,service layer,and display layer,and refine it into five functional modules:data collection,processing,query,analysis,and visualization.Then using Python's Django framework and My SQL database to implement the back-end design of the system,and using ajax technology and Echart library to realize front-end and back-end interaction and front-end data visualization respectively.Finally,the system is fully implemented and the data results are displayed,from which we can better understand the recruitment situation of related positions in the Internet industry.