JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (2): 22-26.doi: 10.6040/j.issn.1672-3961.1.2014.259

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A semi-supervised method based on tree kernel for relationship extraction

LIU Xiaoyong   

  1. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, Guangdong, China
  • Received:2014-03-26 Revised:2014-10-15 Online:2015-04-20 Published:2014-03-26

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Abstract: It was difficult for traditional semi-supervised relation extraction methods to solve "semantic variation" problem. A new semi-supervised relation extraction algorithm based on ensemble learning was prorosed and named L-EC-RE, which used two strategies, one was tree kernel and the other was constrained extension seed set. Experimental study on PopBank benchmark data sets showed that L-EC-RE had better performance than two usual relation extraction algorithms in four assessment criteria, which were Precision, Recall, F-measure and Accuracy.

Key words: relationship extraction, semi-supervised method, semantic variation, tree kernel, support vector machine

CLC Number: 

  • TP181
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