新工科下大数据人才能力与企业需求契合度研究——基于论文和专利的视角  

Research on the Alignment Between Big Data Talent Competenciesand Enterprise Needs Under the New Engineering Paradigm:A Perspective Based on Academic Papers and Patents

作　　者：叶仁道[1] 楼婷玉 袁文静 YE Rendao;LOU Tingyu;YUAN Wenjing(School of Economics,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)

机构地区：[1]杭州电子科技大学经济学院,浙江杭州310018

出　　处：《杭州电子科技大学学报(社会科学版)》2025年第2期54-67,共14页Journal of Hangzhou Dianzi University:Social Sciences

基　　金：浙江省“十四五”教学改革项目(JG20220212)。

摘　　要：基于新工科教育背景,聚焦高校大数据人才培养与企业需求的契合度问题。旨在揭示高校培养模式与企业需求之间的匹配水平,为优化人才培养体系提供理论支撑与实践指导。首先,基于社会网络分析法构建论文和专利技术的共现网络,挖掘学术研究与企业技术需求的关联关系。其次,基于Word2Vec-K-means-LDA的主题挖掘模型,提取不同时间段的核心主题。最后,结合余弦相似度进行主题间的语义匹配测度。结果表明,大数据技术呈现从理论研究到产业应用的演化路径,学术与企业需求在知识图谱、数据挖掘等领域具有较高的契合度。当前高校课程在跨学科融合与实践能力培养方面仍存短板,难以充分满足企业对复合型人才的需求。对此,文章提出构建跨学科培养体系、深化校企协同机制等策略,以提升人才培养效能,支撑大数据产业高质量发展。Against the backdrop of new engineering education,this study focuses on the alignment between university big data talent cultivation and enterprise demands.The aim is to reveal the matching degree between academic training models and industry needs,providing theoretical support and practical guidance for optimizing talent development systems.First,a co-occurrence network of academic papers and patent technologies is constructed using social network analysis to explore the relationship between academic research and enterprise technological needs.Second,a topic mining model based on Word2Vec-K-means-LDA is employed to extract core themes across different time periods.Finally,cosine similarity is used to measure the semantic alignment between topics.The results indicate that big data technology follows an evolutionary path from theoretical research to industrial applications,with strong alignment in areas such as knowledge graphs and data mining.However,university curricula still exhibit shortcomings in interdisciplinary integration and practical skill development,making it challenging to fully meet the demand for interdisciplinary talent in enterprises.In response,this study proposes strategies such as constructing interdisciplinary training systems and deepening university-enterprise collaboration to enhance talent development effectiveness and support the high-quality development of the big data industry.

关 键 词：新工科 大数据人才 能力培养 企业需求 契合度 社会网络分析 

分 类 号：G646[文化科学—高等教育学]