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Relation Extraction Based on Composite Kernel Combining Pattern Similarity of Predicate-Argument Structure

  • Hong-Woo Chun
  • Chang-Hoo Jeong
  • Sa-Kwang Song
  • Yun-Soo Choi
  • Sung-Pil Choi
  • Won-Kyung Sung
Part of the Communications in Computer and Information Science book series (CCIS, volume 264)

Abstract

Lots of valuable textual information is used to extract relations between named entities from literature. Composite kernel approach is proposed in this paper. The composite kernel approach calculates similarities based on the following information: (1) Phrase structure in convolution parse tree kernel that has shown encouraging results. (2) Predicate-argument structure patterns. In other words, the approach deals with syntactic structure as well as semantic structure using a reciprocal method. The proposed approach was evaluated using various types of test collections and it showed the better performance compared with those of previous approach using only information from syntactic structures. In addition, it showed the better performance than those of the state of the art approach.

Keywords

Syntactic Structure Parse Tree Relation Extraction Tree Kernel Candidate Entity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hong-Woo Chun
    • 1
  • Chang-Hoo Jeong
    • 1
  • Sa-Kwang Song
    • 1
  • Yun-Soo Choi
    • 1
  • Sung-Pil Choi
    • 1
  • Won-Kyung Sung
    • 1
  1. 1.Korea Institute of Science and Technology InformationDaejeonSouth Korea

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