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首页> 外文会议>Proceedings of the 2011 ACM/IEEE on joint conference on digital libraries. >Resolving Author Name Homonymy to Improve Resolution of Structures in Co-author Networks
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Resolving Author Name Homonymy to Improve Resolution of Structures in Co-author Networks

机译：解决作者姓名同义字以提高共同作者网络中结构的分辨率

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摘要

We investigate how author name homonymy distorts clustered large-scale co-author networks, and present a simple, effective, scalable and generalizable algorithm to ameliorate such distortions. We evaluate the performance of the algorithm to improve the resolution of mesoscopic network structures, that is those meso-level structures of a network resulting from groupings of nodes and their interlinking. To this end, we establish the ground truth for a sample of author names that is statistically representative of different types of nodes in the co-author network, distinguished by their role for the connectivity of the network. We finally observe that this distinction of node roles based on the mesoscopic structure of the network, in combination with a quantification of the commonality of last names, suggests a new approach to assess network distortion by homonymy and to analyze the reduction of distortion in the network after disambiguation, without requiring ground truth sampling.
机译：我们调查作者姓名同名如何扭曲群集的大型合著者网络，并提出一种简单，有效，可扩展和可推广的算法来改善此类失真。我们评估算法的性能，以提高介观网络结构的分辨率，这是由节点的分组及其相互链接导致的网络的介观级别结构。为此，我们建立了一个作者姓名样本的基本事实，该作者姓名样本在统计上代表了共同作者网络中不同类型的节点，并以其在网络连通性中的作用加以区分。我们最终观察到，基于网络的介观结构对节点角色的这种区分，结合对姓氏的通用性的量化，提出了一种通过同义评估网络失真并分析网络失真减少的新方法。消除歧义后，无需进行地面真相采样。

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