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The European Physical Journal B

, Volume 66, Issue 4, pp 557–561 | Cite as

Empirical analysis on a keyword-based semantic system

Interdisciplinary Physics

Abstract

Keywords in scientific articles have found their significance in information filtering and classification. In this article, we empirically investigated statistical characteristics and evolutionary properties of keywords in a very famous journal, namely Proceedings of the National Academy of Science of the United States of America (PNAS), including frequency distribution, temporal scaling behavior, and decay factor. The empirical results indicate that the keyword frequency in PNAS approximately follows a Zipf’s law with exponent 0.86. In addition, there is a power-low correlation between the cumulative number of distinct keywords and the cumulative number of keyword occurrences. Extensive empirical analysis on some other journals’ data is also presented, with decaying trends of most popular keywords being monitored. Interestingly, top journals from various subjects share very similar decaying tendency, while the journals of low impact factors exhibit completely different behavior. Those empirical characters may shed some light on the in-depth understanding of semantic evolutionary behaviors. In addition, the analysis of keyword-based system is helpful for the design of corresponding recommender systems.

PACS

89.75.-k Complex systems 05.65.+b Self-organized systems 05.10.-a Computational methods in statistical physics and nonlinear dynamics 

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Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Zi-Ke Zhang
    • 1
  • Linyuan Lü
    • 1
  • Jian-Guo Liu
    • 1
    • 2
  • Tao Zhou
    • 1
    • 2
  1. 1.Department of PhysicsUniversity of FribourgFribourgSwitzerland
  2. 2.Department of Modern PhysicsUniversity of Science and Technology of ChinaHefei AnhuiP.R. China

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