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Dynamic Transition of Scientific Teams Based on Time Slicing

机译:基于时间切片的科学团队的动态转型

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Based on dynamic research perspectives of time slicing, this paper shows an endeavor on mining dynamic features of the scientific teams. Traditionally the static method of network structure analysis can successfully be used to analyze the distribution of network resource structure. But it cannot be used to explore the dynamic features of research groups, because of its lacks on the influence of some variables in research activities. These variables include researchers, research hotspots and research funds, etc. which are all in varying state due to the changing world. This paper proposes a new approach to analyze the dynamic characteristics of scientific teams, by using time slicing incorporated with traditional static method. KP(core members Keep-Rate) is used as an index of the dynamic transitions of scientific teams in two sequential time slices, and an algorithm is proposed to identify the successor team(s).
机译:基于时间切片的动态研究视角,本文展示了科学团队采矿动态特征的努力。传统上,网络结构分析的静态方法可以成功地用于分析网络资源结构的分布。但它不能用于探索研究群体的动态特征,因为它缺乏一些变量在研究活动中的影响。这些变量包括研究人员,研究热点和研究资金等。由于变化的世界,这一切都处于不同的状态。本文提出了一种新的方法来分析科学团队的动态特征,通过使用传统的静态方法的时间切片。 KP(核心成员保持率)用作两个连续时间片中科学团队的动态转换的指标,并提出了一种算法来识别继任团队。

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