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Based on Citation Diversity to Explore Influential Papers for Interdisciplinarity

  • Keqiang Wang
  • Chaofeng Sha
  • Xiaoling Wang
  • Aoying Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8709)

Abstract

Interdisciplinary scientific research (IDR) has been obtained more and more attention in recent years. This paper studies the problem of which papers are important for IDR. According to the citation relationships among papers, we focus on the influential papers where novel methods or idea are proposed and these new methods are used in different research areas. A two-stage approach is given to find influential papers for interdisciplinarity based on citation diversity. Firstly, the topic distribution of each paper is estimated by training Latent Dirichlet Allocation (LDA) topic model on the papers repository. Then the diversity of cited papers and citing papers are designed to measure the paper’s influence. The effectiveness of the proposed approach is demonstrated through the extensive experiments on a real dataset and a synthetic dataset.

Keywords

Topic model Diversity Interdisciplinarity 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Keqiang Wang
    • 1
  • Chaofeng Sha
    • 2
  • Xiaoling Wang
    • 1
  • Aoying Zhou
    • 1
  1. 1.Shanghai Key Laboratory of Trustworthy Computing, Institute for Data Science and EngineeringEast China Normal UniversityShanghaiChina
  2. 2.School of Computer Science, Shanghai Key Laboratory of Intelligent Information ProcessingFudan UniversityShanghaiChina

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