Employment Data Services Under The Smart Campus Platform Research On A New Model

In the era of data-driven services,the traditional mode and content of employment services in colleges and universities can no longer meet the dynamic and changing needs of students for employment services,and higher requirements have been put forward for the support of employment services by smart campuses.At present,the construction of China’s smart campus platform is developing rapidly,playing an active role in academic exchange,knowledge sharing and teaching communication.In order to study the mode and realization of employment services under the wisdom campus platform,the elements of employment services under the wisdom campus platform and its characteristics are analyzed,so as to seek the path to transform the data service mode by using the wisdom platform for university employment services and provide reference for the transformation of university employment services.At present,China’s smart campus platform provides services for student users in multiple roles on campus,which has enriched and expanded the ways and levels of university employment departments to serve students.However,the content of China’s university employment services has not yet fully adapted to this trend,and the construction of data services in some universities is not perfect,and the intelligence of the services is not high.Therefore,it is of certain research significance to establish the mode of employment data service under the intelligent campus platform.Firstly,the current situation of employment services in colleges and universities is investigated to understand the characteristics of employment services provided by colleges and universities with the background of smart campus construction,which is summarized into three parts:service objects,service data resource situation and service content.Then,web text mining and questionnaire survey methods are used to study the demand of college students for employment services in colleges and universities.Combining the results of the research on the current situation of employment services under the wisdom campus platform of colleges and universities in China,problems in the collection,provision and mining of data resources of employment services under the current wisdom campus platform are found,which provide support for the subsequent improvement of employment service contents.Then,the employment data service model under the smart campus platform is constructed from the elements of smart services,featuring multiple service subjects,intelligent technology and precise content,with autonomous employment services,precise employment services and student-initiated employment services as the main service processes.To realize this model,in the empirical content of precision-oriented employment service,the Skip-gram model provided by Word2Vec is used to train the job information text with computer major as the basic requirement,to obtain the computer recruitment job industry proximity lexicon,and to calculate the similarity between the five student feature texts and the five job texts accordingly.The calculation results are used as the basis for the smart campus platform to push employment information for students in priority,thus realising a precise type of employment service approach.In the empirical process of proactive employment service,the big data engineer position is divided by industry,and the K-means clustering method is used to obtain the requirements of the position in four different industries and two different levels of competence areas,which is used as the basis for the employment service subject to recommend relevant employment knowledge to students.Finally,the feedback mechanism of employment services relying on the smart campus platform is integrated into the model,aiming to further improve the quality of services with the effectiveness of service outcomes,and to guarantee the integrity and achievability of the model over a long period of time in terms of process and actual operation.