摘要
基于文献计量学的大数据技术热点分析和基子招聘信息的人才需求挖掘,对于高校从“经验主义”教学上升到“数据驱动”培养具有重要的现实意义.使用CiteSpace对1483篇文献进行关键词共现分析,发现研究热点主要集中在数据处理、数据分析及大数据应用三个层面.同时爬取976条招聘信息,通过分词、去除停用词、词频统计进行文本分析,对与技术热点相关的3个招聘岗位进行专业能力统计.根据统计分析结果,从办学层次及特色、专业技术热点、人才需求、团队协作等4个维度对大数据专业课程体系建设提出优化建议.
Based on bibliometrics,the analysis of big data technology hotspots and the mining of talent demand from recruitment information have significant practical implications for universities transitioning from"empirical"teaching to"data-driven"education.By using CiteSpace for keyword co-occurrence analysis on 1483 papers,it was discovered that the main research focuses are primarily in three areas:data processing,data analysis,and big data applications.Meanwhile,976 job postings were collected,and text analysis was conducted through word segmentation,stop word removal,and frequency statistics.Professional competence statistics were conducted for three job positions related to the technological hotspots.Finally,based on the statistical analysis results,optimization suggestions for the construction of the big data professional curriculum system were proposed from four perspectives:educational level and characteristics,professional technology hotspots,talent demand,and team collaboration.
作者
张晶晶
郭丽
郏伯荣
丁永军
ZHANG Jingjing;GUO Li;JIA Borong;DING Yongjun(School of Information Engineering,Lanzhou City University,Lanzhou Gansu 730070;College of Computer Science&Engineering,Northwest Normal University,Lanzhou Gansu 730070)
出处
《甘肃高师学报》
2025年第1期120-125,共6页
Journal of Gansu Normal Colleges
基金
兰州城市学院教学研究与改革项目“创新创业人才培养生态系统构建与运行机理研究”(2024-jy-05)。
关键词
大数据专业
共现图谱
人才需求
课程体系建设
big data major
co-occurrence map
talent demand
curriculum system construction
