云南民族大学学报（自然科学版）2025，Vol.34Issue(5)：590-596,7.DOI:10.3969/j.issn.1672-8513.2025.05.012
基于知识图谱与协同过滤的员工培训推荐研究
Research on employee training recommendation based on knowledge mapping and collaborative filtering
摘要
Abstract
Aiming at the problem of insufficient personalized recommendation due to the generalization of staff training content in power system,a staff training recommendation algorithm based on the combination of knowledge map and collaborative filtering is proposed.First of all,according to the ability requirements of training posts,the knowledge points of employees are divided into six categories of knowledge modules,the comprehensive score of knowledge modules of employees is calculated,and the employee knowledge module scoring matrix is constructed.At the same time,employees are classified according to their professional titles as important labels for personalized recommendation.Secondly,the integrated training evalution standard is used to build a job knowledge graph,and employees' professional titles and scores are combined to generate an employee knowledge mastery graph.Finally,combined with the scoring matrix of employee knowledge module,title tag information and knowledge mastery map,an employee training recommendation model combining knowledge map and collaborative filtering was constructed,personalized recommendations were made for employee training content,and actual training data was used for verification.The results show that compared with LDA topic model,collaborative filtering recommendation algorithm has the highest recommendation accuracy,recall rate and coverage rate in each professional title group.The overall recommendation accuracy,recall rate and coverage rate are increased by 19.29,23.21 and 5.00 percentage points,respectively,to 92.86%,94.48%and 20.36%;The model can effectively solve the problem of data sparsity and realize the personalized recommendation of employee training content.关键词
协同过滤/知识图谱/职称标签/员工培训/个性化推荐Key words
collaborative filtering/knowledge mapping/title label/staff training/personalized recommendation分类
信息技术与安全科学引用本文复制引用
余江龙,苏治文,汪德超,李海龙,马正忠..基于知识图谱与协同过滤的员工培训推荐研究[J].云南民族大学学报（自然科学版）,2025,34(5):590-596,7.基金项目
中国南方电网有限责任公司科技项目(YNKJXM20230135). （YNKJXM20230135）
