Research On Design And Maintenance Management Mechanism Of ZQ Employment Recommendation Platform Based On Big Data

With the number of college graduates reaching a high record in 2017,employment pressure continues unabated.However,the ability of the employment guidance for universities is not enough in our country,at present.And graduates of universities do not get enough of their own career plans.It is difficult to match up to the actual situation in the vast amount of employment information on the Internet.In order to alleviate this contradiction,scholars have joined the research of employment recommendation in the hope of finding an objective method that can be used to recommend employment for individual situations.With the maturity of big data technology.It is no longer a problem for the technology of processing large quantities of data and real-time data.However,big data technology focuses more on the research of recommendations in e-commerce scenarios,and there are few studies on employment recommendations.At present,it lacks recommendation for the large-scale user resumes information,the historical employment information and the recommendation for research on enterprise recruitment needs At the same time,there is a lack of employment information recommendation for users' real-time network behavior preferences.The research is launched in this context.With the development and application of big data technologies,large-scale distributed data processing technologies,large-scale text mining technologies,data real-time online and offline processing technologies have been increasingly put into practice.Based on this,the study started to use the big data technology to dig deeper into the pain points in the user's personalized employment recommendation,identify a variety of recommended scenarios,diverge a variety of recommendation programs and make the recommendation effective and complete.First of all,this study explores the stakeholder theory,the bilateral platform theory,and the platform company growth theory.These theories centered on the construction of the platform,the maintenance management,and put forward the platform bilateral interest relations,stakeholders of the construction platform.What's more,the research came up with the six elements of the healthy growth of the platform.At the same time,which using the method of bibliometrics to discusse the research status of employment recommendation platform,the application of big data in employment recommendation platform and the research on big data recommendation algorithm.And using of web crawler technology creatively to understand of the recommended functions and status of the same type of recommended platform,which can provide reference for the study of the platform.Based on the analysis of the platform requirements,the overall design and function implementation of the ZQ big data employment recommendation platform was implemented using the big data crawler technology,big data architecture technology,text mining technology,and database technology.The recommendation based on real-time user online behavior data,user history information and the mixed recommendation to get the employment attributes of student improve the employment recommendation accuracy rate.It was established from the perspective of stakeholders,which based on platform construction,an initial platform operation and maintenance management mechanism.However,it is not obvious enough for the effectiveness of the employment recommendation platform based on big data.Therefore,the effect of the operation and recommendation of the research are worth further observation after the landing of the platform.It still needs a lot of energy to the research and discussion of employment recommendation platforms based on big data.