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An Empirical Research on Extracting Relations from Wikipedia Text

  • Jin-Xia Huang
  • Pum-Mo Ryu
  • Key-Sun Choi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5326)

Abstract

A feature based relation classification approach is presented, in which probabilistic and semantic relatedness features between patterns and relation types are employed with other linguistic information. The importance of each feature set is evaluated with Chi-square estimator, and the experiments show that, the relatedness features have big impact on the relation classification performance. A series experiments are also performed to evaluate the different machine learning approaches on relation classification, among which Bayesian outperformed other approaches including Support Vector Machine (SVM).

Keywords

Information extraction relation classification feature-based relatedness information 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jin-Xia Huang
    • 1
  • Pum-Mo Ryu
    • 1
  • Key-Sun Choi
    • 1
  1. 1.SWRC, Computer Science Division, EECS Dept. KAISTDaejeonRepublic of Korea

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