吉林大学学报（信息科学版）2026，Vol.44Issue(2)：446-452,7.
高职院校毕业生就业系统多种类资源按需推荐算法
On-Demand Recommendation Algorithm for Various Types of Resources in Employment System of Higher Vocational College Graduates
摘要
Abstract
Due to the large number of user groups and resources in the employment system for vocational college graduates,the weight of employment resources varies significantly,making it difficult to generate recommendation labels uniformly,resulting in the inability of the graduate employment system to complete on-demand resource recommendations.Therefore,a multi type resource on-demand recommendation algorithm is designed for the employment system of vocational college graduates.By extracting multidimensional features of user information from historical data and utilizing long short-term memory neural networks to fuse multiple sources of data,effective labels are extracted to establish a user label library for the graduate employment system,forming user profiles.Based on the general situation of user profiles,combined with the Ebbinghaus forgetting curve,the label matrix of multiple types of employment resources is evaluated,a content topic model is established,and spectral clustering algorithm is used for graph segmentation.Different weight values are assigned to different employment resources based on similarity,and normalization is implemented to generate secondary labels,completing the labeling process of employment resources.A regional preference base for graduates'employment is constructed,associating and matching user profiles with employment resource labels in designated geographical locations,and score the recommendation results through expert ranking weighting.Experiments are conducted on the above design,and the results show that the hit rate of the algorithm's recommended results is greater than 0.9,indicating high accuracy.关键词
就业系统/按需推荐/多维特征/用户画像/标签矩阵Key words
employment system/recommend on demand/multidimensional features/user portrait/label matrix分类
信息技术与安全科学引用本文复制引用
刘梦遥,王一佼,孙鸿炜,苏金玲..高职院校毕业生就业系统多种类资源按需推荐算法[J].吉林大学学报（信息科学版）,2026,44(2):446-452,7.基金项目
陕西省教育厅一般专项科学研究计划基金资助项目(24JK0037) （24JK0037）
