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A Consensus-Based Method to Enhance a Recommendation System for Research Collaboration

机译:基于共识的方法来增强研究协作推荐系统

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With the development of scientific societies, research problems are increasingly complex, requiring scientists to collaborate to solve them. The quality of collaboration between researchers is a major factor in determining their achievements. This study proposes a collaboration recommendation method that takes into account previous research collaboration and research similarities. Research collaboration is measured by combining the collaboration time and the number of co-authors who already collaborated with an author. Research similarity is based on authors' previous publications and academic events they attended. In addition, a consensus-based algorithm is proposed to integrate bibliography data from different sources, such as the DBLP Computer Science Bibliography, ResearchGate, CiteSeer, and Google Scholar. The experimental results show that this proposal improves the accuracy of the recommendation systems, in comparison with other methods.
机译:随着科学社会的发展,研究问题变得越来越复杂,需要科学家们共同解决。研究人员之间的协作质量是决定其成就的主要因素。这项研究提出了一种协作推荐方法,该方法考虑了以前的研究协作和研究相似性。研究协作是通过将协作时间和已经与作者合作的合著者数量相结合来衡量的。研究的相似性基于作者以前的出版物和他们参加的学术活动。此外,提出了一种基于共识的算法来集成来自不同来源的书目数据,例如DBLP计算机科学书目,ResearchGate,CiteSeer和Google Scholar。实验结果表明,与其他方法相比,该建议提高了推荐系统的准确性。

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