Weak Ties Based Recommendation for Interdisciplinary Research Collaboration

Won Kyung Lee, S. Sohn
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Abstract

This study investigates recommendations for interdisciplinary research collaboration based on the weak ties theory. Contents-based features are proposed to recommend interdisciplinary collaboration considering that some researchers who have shown a preference for interdisciplinary collaboration could be connected even if they have dissimilar research profiles. Therefore, we inferred the preference of interdisciplinary research collaboration for every researcher, and considered features such as highlighting dissimilar researchers depending on their preferences. The features are designed to have typical similarity measures when the researchers do not prefer interdisciplinary research collaboration. We evaluated our proposed features with the baseline features of patent application datasets and the former methods outperformed the latter methods.
基于弱联系的跨学科研究合作推荐
本研究探讨基于弱联系理论的跨学科研究合作建议。考虑到一些具有跨学科合作偏好的研究人员即使具有不同的研究概况也可以被连接起来,提出了基于内容的特征来推荐跨学科合作。因此,我们推断了每个研究人员对跨学科研究合作的偏好,并考虑了根据他们的偏好突出不同研究人员等特征。当研究人员不喜欢跨学科研究合作时,这些特征被设计成具有典型的相似性度量。我们将我们提出的特征与专利申请数据集的基线特征进行了评估,结果表明前一种方法优于后一种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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