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Composing Scientific Collaborations Based on Scholars' Rank in Hypergraph

机译:基于超图学者排名的科学合作

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摘要

Finding the right scholars for collaboration is crucial for scientific progress. In this study, a novel algorithm is proposed to find the successful team configurations for scientific collaboration in the presence of the collaboration network of scholars. In this algorithm, the collaboration network is exploited to estimate the trust level among team members and the skill level of the scholars, while a hypergraph is used to model the relations. Also, our algorithm improves the search process by directing it to the promising regions, where the probability of finding the successful teams is high. A comparison with other algorithms is done to evaluate the proposed algorithm, using the similarity to successful collaborations. Our findings show that this algorithm achieves a significantly higher performance, compared to the other algorithms.
机译:寻找合适的学者进行合作对于科学进步至关重要。在这项研究中,提出了一种新颖的算法,可以在存在学者协作网络的情况下为科学协作找到成功的团队配置。在该算法中,利用协作网络估计团队成员之间的信任度和学者的技能水平,同时使用超图对关系进行建模。同样,我们的算法通过将搜索引擎引向有希望的区域,从而找到成功的团队的可能性很高,从而改善了搜索过程。使用与成功协作的相似性,与其他算法进行比较以评估所提出的算法。我们的发现表明,与其他算法相比,该算法可实现更高的性能。

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