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The Data Set of CNC machine tools field key core technology identification

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科学数据银行2025-02-18 更新2026-04-23 收录
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[Objective] Combining textual content features and the complex network relationship between “science and technology”, this study conducts research on the identification method of key core technologies, aiming to provide intelligence support for governments, research institutions, and the industry to rationally formulate scientific and technological strategic plans, or carry out scientific and technological innovation activities. [Methods] The Sentence-BERTopic model is used to perform deep semantic fusion and knowledge topic clustering on sentence-level paper and patent text corpora. Based on the citation relationships of papers and patents, a “science-technology” knowledge topic complex network is constructed, and the traditional PageRank algorithm is improved by combining node quality characteristics, time decay factors, weights of incoming node edges, and outdegree, etc., to objectively rank the importance and influence of nodes in the field. Finally, key core technologies are selected in combination with the head/tail breaks method. [Results] An empirical study was conducted in the field of numerical control machines, resulting in the identification of 53 key core technologies, including thermal error modeling and compensation, numerical control machine tool control technology, and numerical control machine tool feed systems. When compared with relevant domestic and international policy plans, this outcome comprehensively encompassed the key core technologies within the domain, thereby demonstrating the scientific validity and rationality of the methodology employed.

[研究目标] 本研究融合文本内容特征与“科技”领域复杂网络关联关系,针对关键核心技术识别方法展开研究,旨在为政府、科研机构及产业界合理制定科技战略规划、开展科技创新活动提供情报支撑。[研究方法] 本研究采用Sentence-BERTopic模型,对句子级论文与专利文本语料库开展深度语义融合与知识主题聚类;基于论文与专利的引用关系,构建“科技”知识主题复杂网络;结合节点质量特征、时间衰减因子、入边权重及出度等要素,对传统PageRank算法进行改进,以客观排序该领域内节点的重要性与影响力;最终结合头尾分割法筛选出关键核心技术。[研究结果] 本研究以数控机床领域为对象开展实证研究,共识别出53项关键核心技术,涵盖热误差建模与补偿、数控机床控制技术、数控机床进给系统等方向。将该识别结果与国内外相关政策规划对比后发现,其全面覆盖了该领域的关键核心技术,验证了所提方法的科学性与合理性。
提供机构:
cao kun
创建时间:
2024-03-26
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