A Network Maximum Flow Based Approach for
 Author Name Disambiguation

doi:10.16183/j.cnki.jsjtu.2020.02.001

Abstract

Abstract: In order to reduce the influence of sharing features (organizations, conferences, etc.) among different author entities on author name disambiguation, an algorithm based on network maximum flow is proposed in this paper. The algorithm puts the paper entities and features into a network graph, and sets the capacity of feature nodes based on the sharing degree. And then, it calculates maximum flow between each paper nodes and does clustering based on maximum flow. The experiment results show that the proposed algorithm has a more balanced performance on accuracy and recall, and has better overall performance.

Key words: name disambiguation; maximum flow; clustering; academic network

CLC Number:

TP 391

QUAN Jinqi,FU Luoyi,GAN Xiaoying,WANG Xinbing. A Network Maximum Flow Based Approach for Author Name Disambiguation[J]. Journal of Shanghai Jiaotong University, 2020, 54(2): 111-116.

References ［14］

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A Network Maximum Flow Based Approach for Author Name Disambiguation

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