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Extraction of Relationships between Scientific Terms based on Composite Kernels  

Choi, Sung-Pil (한국과학기술정보연구원 정보기술연구실)
Choi, Yun-Soo (한국과학기술정보연구원 정보기술연구실)
Jeong, Chang-Hoo (한국과학기술정보연구원 정보기술연구실)
Myaeng, Sung-Hyon (한국과학기술원 전산학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.15, no.12, 2009 , pp. 988-992 More about this Journal
Abstract
In this paper, we attempted to extract binary relations between terminologies using composite kernels consisting of convolution parse tree kernels and WordNet verb synset vector kernels which explain the semantic relationships between two entities in a sentence. In order to evaluate the performance of our system, we used three domain specific test collections. The experimental results demonstrate the superiority of our system in all the targeted collection. Especially, the increase in the effectiveness on KREC 2008, 8% in F1, shows that the core contexts around the entities play an important role in boosting the entire performance of relation extraction.
Keywords
Relation Extraction; Kernel Methods; Composite Kernel; Convolution Parse Tree Kernel; WordNet Synset Kernel; Machine Learning;
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