招聘网站数据薪资K-means聚类分析可视化  

Visualization of K⁃means clustering analysis for recruitment website data salary

作　　者：杜宇灏 闫长青[1] 李环宇[1] Du Yuhao;Yan Changqing;Li Huanyu(Intelligent Equipment College,Shandong University of Science&Technology,Tai’an 271000,China)

机构地区：[1]山东科技大学智能装备学院,泰安271000

出　　处：《现代计算机》2023年第23期64-68,91,共6页Modern Computer

基　　金：全国统计科学研究项目(一般课题)(2020LY085)。

摘　　要：该研究利用BOSS直聘网站上的岗位数据,使用Python编程语言通过K-means聚类算法对不同岗位的薪资水平进行分析和可视化展示。通过多次迭代计算,将岗位样本点分配到最近的聚类中心,并更新聚类中心的位置。最终的可视化结果显示了不同学历,不同薪资水平类别的岗位样本点的分布情况和每个聚类中心的位置。这些结果对求职者和招聘人员来说具有重要意义。求职者可以根据不同薪资水平类别的分布情况选择更符合自身期望的岗位,而招聘人员则可以更好地了解市场上不同薪资水平的竞争态势,制定更合理的薪资策略。This study utilizes job data from the Boss Zhipin website and employs Python programming language to analyze and visually present the salary levels of different positions using the K-means clustering algorithm.Through multiple iterations,job samples are assigned to the nearest cluster centers and the positions of these centers are updated.The final visualization results de-pict the distribution of job samples in different salary level categories and the positions of each cluster center.These findings hold significant implications for both job seekers and recruiters.Job seekers can make informed choices by considering the distribution of different salary level categories and selecting positions that align with their expectations.On the other hand,recruiters can gain deeper insights into the competitive landscape of various salary levels in the market,enabling them to formulate more reasonable salary strategies.

关 键 词：BOSS直聘 K-MEANS聚类 薪资 可视化 

分 类 号：F249.24[经济管理—劳动经济] TP311.13[经济管理—国民经济]