A local tree alignment approach to relation extraction of multiple arguments.
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- Title
- A local tree alignment approach to relation extraction of multiple arguments.
- Authors
- Seokhwan Kim; Minwo Jeong; Lee, GG
- Date Issued
- 2011-07
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Abstract
- In this paper, we address the problem of relation extraction of multiple arguments where the relation of entities is framed by multiple attributes. Such complex relations are successfully extracted using a syntactic tree-based pattern matching method. While induced subtree patterns are typically used to model the relations of multiple entities, we argue that hard pattern matching between a pattern database and instance trees cannot allow us to examine similar tree structures. Thus, we explore a tree alignment-based soft pattern matching approach to improve the coverage of induced patterns. Our pattern learning algorithm iteratively searches the most influential dependency tree patterns as well as a control parameter for each pattern. The resulting method outperforms two baselines, a pairwise approach with the tree-kernel support vector machine and a hard pattern matching method, on two standard datasets for a complex relation extraction task. (C) 2010 Elsevier Ltd. All rights reserved.
- Keywords
- Relation extraction; Multiple arguments; Pattern induction; Local tree alignment; Soft pattern matching
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/17414
- DOI
- 10.1016/J.IPM.2010.12.002
- ISSN
- 0306-4573
- Article Type
- Article
- Citation
- Information Processing & Management, vol. 47, no. 4, page. 593 - 605, 2011-07
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