TY -的A2 - 1月,面Ahmad盟——周,燕PY - 2023 DA - 2023/02/10 TI -大学教师的发展和培训策略基于数据挖掘技术的SP - 7103391六世- 2023 AB——增加教育投资在中国,高等教育机构的教师有更高的要求。本研究主要探讨大学教师的发展和培训策略基于数据挖掘技术。数据挖掘技术是致力于数据分析和理解、揭示的技术数据中包含的信息。这是一个领域的前沿研究课题信息和数据库技术。因此,大学教学质量的监测和评价系统基于数据挖掘是专为高校教育事务的管理提供了方便。本文选择一个无监督分类方法:聚类分析。这种方法不仅可以获得合理的分类结果也给员工发展的全面性考虑并给予合理的发展建议每个员工通过分类结果。的一系列介绍老师的信息,人事管理模块应提供以下功能:教师信息管理、合同信息管理、老师辞职的信息管理和查询人员信息。招聘管理模块经常收集候选人信息,寄存器和存储,然后进行一系列的人员根据招聘标准筛查这些候选人,最后决定了可能的候选人。之后,一系列的综合评价进行这些选定的候选人,最后录取的候选人选择基于候选人的综合性能。 The K-means clustering algorithm in the cluster analysis method is adopted. This algorithm has the excellent characteristics of high computational efficiency and is suitable for the operation of large amount of data. Through the clustering algorithm, a reasonable assessment method is established, and it is effectively used in the human resources assessment management system. Among the introduced teachers, the number of teachers whose professional title is high, the highest degree is doctorate, and the number of teachers whose papers are published at SCI level accounts for 16%. The data tested by the data mining tool contains 1,400 rows of data. The minimum support is 5%, and the minimum confidence is 90%. This study is helpful for the rational planning of human resources and the promotion of comprehensive competitiveness of colleges and universities. SN - 1574-017X UR - https://doi.org/10.1155/2023/7103391 DO - 10.1155/2023/7103391 JF - Mobile Information Systems PB - Hindawi KW - ER -