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Author Influence Spreading Prediction Based on Co-Citation Interest Similarity

机译:作者基于共同引发兴趣相似性影响传播预测

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摘要

In the previous research, the assessment of author's influence is mainly based on the historical information of literature, such as the number of author's publications and times cited, and the reference relationship. However, the author influence is not only reflected in the amount of static data, but also in the behavior that the author's point of view is noticed and communicated. Meanwhile, the influence spreads through the relational path of cooperation and citation between authors, on which the authors should have similar academic interests. Therefore, this paper proposed an influence spreading model with the author's co-citation interest similarity and the path of citation and cooperation. On the basis of this, a novel algorithm of influence spreading prediction is designed, and carried on the experiment verification using the public literature information resources. The results of AUC indicator show the effectiveness on the proposed method.
机译:在以前的研究中,作者的影响的评估主要基于文学的历史信息,例如作者的出版物和时代的历史信息以及参考关系。然而,作者的影响不仅反映在静态数据的数量,而且在作者的观点被注意到和传达的行为中。同时,作者应该通过作者之间的合作和引用的关系路径传播,作者应该具有类似的学业兴趣。因此,本文提出了作者共同引用兴趣相似性和引文与合作路径的影响模型。在此基础上,设计了一种新颖的影响扩展预测算法,并使用公共文献信息资源进行实验验证。 AUC指标的结果表明了该方法的有效性。

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