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Incorporating User Feedback into Name Disambiguation of Scientific Cooperation Network

  • Yuhua Li
  • Aiming Wen
  • Quan Lin
  • Ruixuan Li
  • Zhengding Lu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6897)

Abstract

In scientific cooperation network, ambiguous author names may occur due to the existence of multiple authors with the same name. Users of these networks usually want to know the exact author of a paper, whereas we do not have any unique identifier to distinguish them. In this paper, we focus ourselves on such problem, we propose a new method that incorporates user feedback into the model for name disambiguation of scientific cooperation network. Perceptron is used as the classifier. Two features and a constraint drawn from user feedback are incorporated into the perceptron to enhance the performance of name disambiguation. Specifically, we construct user feedback as a training stream, and refine the perceptron continuously. Experimental results show that the proposed algorithm can learn continuously and significantly outperforms the previous methods without introducing user interactions.

Keywords

Name Disambiguation User Feedback Scientific Cooperation Network Perceptron Constraint 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yuhua Li
    • 1
  • Aiming Wen
    • 1
  • Quan Lin
    • 1
  • Ruixuan Li
    • 1
  • Zhengding Lu
    • 1
  1. 1.Intelligent and Distributed Computing Lab, School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanP.R. China

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