Since the concept of cooperative consumption was proposed,the sharing economy has become the topic of highest concern in the academic world.From the perspective of the economic market,the sharing economy has created a...Since the concept of cooperative consumption was proposed,the sharing economy has become the topic of highest concern in the academic world.From the perspective of the economic market,the sharing economy has created a new model that breaks the original economic order,which can accommodate more labor.Compared with traditional employment methods,the sharing economy has undergone significant changes in terms of labor.The sharing economy is extremely dependent on information technology,and the employment relationship is relatively vague.This poses great challenges to the welfare,income security,and stability of college graduates’employment.This paper explores and analyzes the new employment methods from the perspective of the sharing economy.展开更多
The use of machine learning to predict student employability is important in order to analyse a student’s capability to get a job.Based on the results of this type of analysis,university managers can improve the empl...The use of machine learning to predict student employability is important in order to analyse a student’s capability to get a job.Based on the results of this type of analysis,university managers can improve the employability of their students,which can help in attracting students in the future.In addition,learners can focus on the essential skills identified through this analysis during their studies,to increase their employability.An effectivemethod calledOPT-BAG(OPTimisation of BAGging classifiers)was therefore developed to model the problem of predicting the employability of students.This model can help predict the employability of students based on their competencies and can reveal weaknesses that need to be improved.First,we analyse the relationships between several variables and the outcome variable using a correlation heatmap for a student employability dataset.Next,a standard scaler function is applied in the preprocessing module to normalise the variables in the student employability dataset.The training set is then input to our model to identify the optimal parameters for the bagging classifier using a grid search cross-validation technique.Finally,the OPT-BAG model,based on a bagging classifier with optimal parameters found in the previous step,is trained on the training dataset to predict student employability.The empirical outcomes in terms of accuracy,precision,recall,and F1 indicate that the OPT-BAG approach outperforms other cutting-edge machine learning models in terms of predicting student employability.In this study,we also analyse the factors affecting the recruitment process of employers,and find that general appearance,mental alertness,and communication skills are the most important.This indicates that educational institutions should focus on these factors during the learning process to improve student employability.展开更多
The effective operation of school-enterprise cooperation is of great strategic significance to promote college students to achieve employment of high-quality.Therefore,this paper will make a detailed discussion on the...The effective operation of school-enterprise cooperation is of great strategic significance to promote college students to achieve employment of high-quality.Therefore,this paper will make a detailed discussion on the effect that school-enterprise cooperation accelerates college students to achieve employment in good quality,hoping that it can provide the necessary guidance information to the researchers in this field.展开更多
基金An analysis of the work path of graduate students staying in cities under the background of urban transformation,DSGB2020109,Daqing City Philosophy and Social Science Planning Research ProjectThe construction and practice of the“four in one”collaborative education model of school-enterprise under the background of transformation--Taking Heilongjiang Bayi Agricultural University as an example of animal science and animal medicine,SJGY20170445,Heilongjiang Province Higher Education Teaching Reform ProjectResearch on the incentive mechanism for innovation and entrepreneurship of animal husbandry and veterinary professionals from the perspective of demand analysis,GBB1317082,a key subject of the 13th Five-Year Plan for Education Science in Heilongjiang Province.
文摘Since the concept of cooperative consumption was proposed,the sharing economy has become the topic of highest concern in the academic world.From the perspective of the economic market,the sharing economy has created a new model that breaks the original economic order,which can accommodate more labor.Compared with traditional employment methods,the sharing economy has undergone significant changes in terms of labor.The sharing economy is extremely dependent on information technology,and the employment relationship is relatively vague.This poses great challenges to the welfare,income security,and stability of college graduates’employment.This paper explores and analyzes the new employment methods from the perspective of the sharing economy.
文摘The use of machine learning to predict student employability is important in order to analyse a student’s capability to get a job.Based on the results of this type of analysis,university managers can improve the employability of their students,which can help in attracting students in the future.In addition,learners can focus on the essential skills identified through this analysis during their studies,to increase their employability.An effectivemethod calledOPT-BAG(OPTimisation of BAGging classifiers)was therefore developed to model the problem of predicting the employability of students.This model can help predict the employability of students based on their competencies and can reveal weaknesses that need to be improved.First,we analyse the relationships between several variables and the outcome variable using a correlation heatmap for a student employability dataset.Next,a standard scaler function is applied in the preprocessing module to normalise the variables in the student employability dataset.The training set is then input to our model to identify the optimal parameters for the bagging classifier using a grid search cross-validation technique.Finally,the OPT-BAG model,based on a bagging classifier with optimal parameters found in the previous step,is trained on the training dataset to predict student employability.The empirical outcomes in terms of accuracy,precision,recall,and F1 indicate that the OPT-BAG approach outperforms other cutting-edge machine learning models in terms of predicting student employability.In this study,we also analyse the factors affecting the recruitment process of employers,and find that general appearance,mental alertness,and communication skills are the most important.This indicates that educational institutions should focus on these factors during the learning process to improve student employability.
文摘The effective operation of school-enterprise cooperation is of great strategic significance to promote college students to achieve employment of high-quality.Therefore,this paper will make a detailed discussion on the effect that school-enterprise cooperation accelerates college students to achieve employment in good quality,hoping that it can provide the necessary guidance information to the researchers in this field.
