计算机与数字工程2025，Vol.53Issue(2)：486-492,7.DOI:10.3969/j.issn.1672-9722.2025.02.033
基于线性二次指数平滑法的高校毕业生就业去向预测方法
A Forecasting Method of College Graduates'Employment Destinations Based on Linear Quadratic Exponential Smoothing Method
摘要
Abstract
Aiming at the problems of poor classification accuracy of college graduates'employment resources information and low accuracy of employment destination prediction results,this paper puts forward a prediction method of college graduates'employ-ment destination based on linear quadratic exponential smoothing method.This paper constructs an analysis model of influencing fac-tors of college graduates'employment,predicts the employment rate of college students by using random forest method,and classi-fies the results.Using Apriori method,this paper analyzes the correlation between job-seeking information and job-seeking require-ments of college graduates.The first exponential smoothing method is used to analyze the standard error between the type of employ-ment unit and the salary range.On this basis,the second smoothing value is estimated,and the weight of the employment destina-tion category of college graduates to be estimated is adjusted through the second smoothing value of employment information catego-ry,so as to reduce the prediction error of the employment destination of college graduates and realize the employment destination prediction of college graduates.The experimental results show that the proposed method has high accuracy and recall rate in predict-ing the employment destination of graduates,and can effectively recommend reasonable enterprise positions for college graduates.关键词
线性二次指数平滑法/就业数据挖掘/就业信息样本聚类/就业去向预测Key words
linear quadratic exponential smoothing method/employment data mining/employment information sample clus-tering/employment destination forecast分类
计算机与自动化引用本文复制引用
蒋大锐,徐胜超..基于线性二次指数平滑法的高校毕业生就业去向预测方法[J].计算机与数字工程,2025,53(2):486-492,7.基金项目
国家自然科学基金面上项目(编号:61772221) （编号:61772221）
广州华商学院校内导师制科研项目(编号:2024HSDS27) （编号:2024HSDS27）
广州华商学院2023年创新创业教育专项研究课题(编号:HS2023CXCY04)资助. （编号:HS2023CXCY04）
