| 王晓琳1 孙英泽 1 闫 雪 1, 2.基于作者自相关和合作相关的创新团队挖掘方法研究[J].中国科技资源导刊,2025,(3):17~27 |
| 基于作者自相关和合作相关的创新团队挖掘方法研究 |
| Research on Innovative Team Mining Method Based on Author Self-relevancy and Cooperation Relevance |
| 投稿时间：2025-01-03 |
| DOI： |
| 中文关键词: 创新团队;自相关;合作相关;团队挖掘 |
| 英文关键词: innovation team, self-relevancy, collaboration relevance, team mining |
| 基金项目:中国水产科学研究院基本科研业务费项目“国内外优秀渔业科技创新团队竞争力特征分析”(2022B002);中国水产科学研究院中央级公益性科研院所基本科研业务费专项“国际渔业科技与产业发展动态研究”(2022GH07) |
| 作者 | 单位 | | 王晓琳1 孙英泽 1 闫 雪 1, 2 | (1. 中国水产科学研究院，北京 100141
2. 中国人民大学图书馆，北京 100872) |
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| 摘要点击次数: 17 |
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| 中文摘要: |
| 科技创新团队逐渐成为科研活动的基本单元，团队评价日益重要，在某领域团队评价中，评价主体即创新团队的挖掘识别是评价难点。基于空间向量模型，结合作者贡献计算作者合作相关度，构建作者合作关系矩阵。提出基于作者自相关度、作者合作相关度的创新团队挖掘方法，并辅助利用凝聚子群的k-核算法开展创新团队挖掘。以水产生物技术领域为例开展实证研究，并将基于文献计量指标挖掘创新团队方法和基于模块度社区发现算法挖掘创新团队方法进行比较，对比验证确定这个方法的精确率、召回率、F1值均高于其他两种方法，适用于与实际团队相似的小规模核心团队挖掘，团队成果覆盖率高达92.5%，对后续团队成果评价的影响较小，具备有效性和可行性。 |
| 英文摘要: |
| Technology innovation teams are gradually becoming the fundamental units of scientific research activities, and team evaluation is increasingly crucial. In the evaluation of teams within a certain field, identifying and recognizing innovative teams pose a challenging aspect of the assessment. The article was based on the spatial vector model, combining author contributions to calculate the relevance of author collaboration, and constructing an author collaboration matrix. An innovative team mining method based on author self- relevancy and cooperative relevancy is proposed, and the k-accounting method of coacervated subgroups is used to carry out innovation team mining. Take aquatic biotechnology as an example to carry out empirical research. Through comparison and verification, it is determined that the precision, recall and F1-score of this method are higher than the other two methods, which are suitable for small-scale core team mining similar to the actual team, and the coverage rate of team results was as high as 92.5%, which had little impact on the follow-up team results evaluation, and was effective and feasible. |
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