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Node importance measure for scientific research collaboration from hypernetwork perspective

机译:超网络视角下科研合作的节点重要性度量

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Collaboration has become main stream and trend in interdisciplinary fields. In research collaboration organizations, to evaluate the contributions of researchers to the organization and then to identify core researchers is an important issue to carry out performance appraisal and crisis management of brain drain. Scientific research collaboration network is a basic model to investigate this question, but under the context of increasingly complex collaborative behaviour, it shows its limitations for semantic representations. In this paper, by introducing hypernetwork, a more powerful modelling tool than traditional network, and taking scientific paper co-authorship as object to construct scientific research collaboration hypernetwork (SRCH), we measure the importance of researchers in two aspects, as collaborative relationship structure and collaborative achievement value from a hypernetwork perspective. An additive weighting method with adjustable parameters is utilized to integrate the evaluation indicators of the two aspects, and then the synthetical importance evaluation of researchers is obtained. Analysis of data instance verifies that our node importance measure for scientific research collaboration from hypernetwork perspective is reasonable and effective.
机译:合作已成为跨学科领域的主流和趋势。在研究协作组织中,评估研究人员对组织的贡献,然后确定核心研究人员是进行绩效评估和人才流失危机管理的重要问题。科学研究协作网络是研究此问题的基本模型,但是在协作行为日益复杂的背景下,它显示了语义表示的局限性。在本文中,通过介绍比传统网络更强大的建模工具超网络,并以科学论文的共同作者为对象来构建科研协作超网络(SRCH),我们从两个方面衡量研究人员的重要性,即协作关系结构从超网络的角度来看协作成就价值。利用参数可调整的加性加权方法对两个方面的评价指标进行综合,得到研究人员的综合重要性评价。数据实例分析验证了我们从超网络的角度对科研合作进行节点重要性度量是合理有效的。

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