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Predicting Research Collaboration Trends Based on the Similarity of Publications and Relationship of Scientists

机译:基于出版物的相似性和科学家之间的关系预测研究合作趋势

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Nowadays, collaboration is indispensable in solving increasingly complex problems. In the academic context, research collaboration influences many aspects of research problems approached. The research collaboration is beneficial for scientists, especially early-career scientists, to determine potential successful collaborations. Predicting the trend of collaboration is an important step in improving the quality of research collaboration between scientists. In this study, we propose a method for predicting research collaboration trends by taking into account the research similarity and the relationship between scientists. The research similarity is computed by considering the author's profiles. The co-author graph is built to explore new collaborators based on the connections weigh between scientists. We are currently in the process of developing a real system and our system shows promising results in predicting the potential success collaborators.
机译:如今,协作对于解决日益复杂的问题是必不可少的。在学术背景下,研究合作会影响所研究问题的许多方面。研究合作对科学家,尤其是早期职业科学家,有利于确定潜在的成功合作。预测合作趋势是提高科学家之间研究合作质量的重要一步。在这项研究中,我们提出了一种通过考虑研究相似性和科学家之间的关系来预测研究合作趋势的方法。通过考虑作者的个人资料来计算研究相似度。共同作者图旨在根据科学家之间的权衡关系探索新的合作者。我们目前正在开发一个真实的系统,并且我们的系统在预测潜在的成功协作者方面显示出可喜的结果。

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