科研成果的自动化归属模型研究  

Research on Automatic Identification Model of Academic Achievements'Institutional Affiliation

作　　者：叶曾瑜 Ye Zengyu(South China Normal University Library)

机构地区：[1]华南师范大学图书馆

出　　处：《信息与管理研究》2025年第1期78-86,共9页Journal of Information and Management

摘　　要：在计算机技术高速发展的时代,数据量的急剧增长以及工作生活节奏的加快,对图书馆馆员的服务质量和效率提出了更高的要求。在“破五唯”背景下,各大高校逐步拓宽教师的业绩评判标准,在科研成果方面,主要包括专利和论文等,而专利和部分中文论文数据存在发明人或作者无法与单位对应的难题。为了更好地解决这个问题,本研究从WOS数据出发,基于Python以及社会网络分析,构建并优化模型,探索数据自动化处理和机构归属判断的方法,提高了学科服务的效率和质量,同时为未来专利及部分中文论文的机构归属研究提供了参考。In the era of rapid development of computer technology,with the increase in data volume and the acceleration of work and life rhythm,higher requirements are placed on the librarians'service quality and efficiency.In the context of“Breaking the Five Only”,major universities have gradually broadened the evaluation criteria for teachers'performance.Academic achievements are mainly evaluated based on patents and papers.There are difficulties in relating inventors or authors to their affiliations in the data of patents and some Chinese papers.To better solve the problem,this study starts with WOS data,builds and optimizes models based on Python and social network analysis,and explores the methods for automated data processing and institutional affiliation identification.It improves the efficiency and quality of subject services and provides a reference for future research on the institutional affiliation of patents and some Chinese papers.

关 键 词：科研成果评价 机构归属认定 社会网络分析 数据自动化处理 数据治理 

分 类 号：G250.7[文化科学—图书馆学]