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| A feature-enriched tree kernel for relation extraction | |
| Sun, Le (1); Han, Xianpei (1) | |
| 2014 | |
| Conference Name | 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 |
| Pages | 61-67 |
| Conference Date | June 22, 2014 - June 27, 2014 |
| Conference Place | Baltimore, MD, United states |
| Indexed Type | EI |
| Publish Place | Association for Computational Linguistics (ACL) |
| ISBN | 9781937284732 |
| Department | (1) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, HaiDian District, Beijing, China |
| English Abstract | Tree kernel is an effective technique for relation extraction. However, the traditional syntactic tree representation is often too coarse or ambiguous to accurately capture the semantic relation information between two entities. In this paper, we propose a new tree kernel, called feature-enriched tree kernel (FTK), which can enhance the traditional tree kernel by: 1) refining the syntactic tree representation by annotating each tree node with a set of discriminant features; and 2) proposing a new tree kernel which can better measure the syntactic tree similarity by taking all features into consideration. Experimental results show that our method can achieve a 5.4% F-measure improvement over the traditional convolution tree kernel. © 2014 Association for Computational Linguistics.; Tree kernel is an effective technique for relation extraction. However, the traditional syntactic tree representation is often too coarse or ambiguous to accurately capture the semantic relation information between two entities. In this paper, we propose a new tree kernel, called feature-enriched tree kernel (FTK), which can enhance the traditional tree kernel by: 1) refining the syntactic tree representation by annotating each tree node with a set of discriminant features; and 2) proposing a new tree kernel which can better measure the syntactic tree similarity by taking all features into consideration. Experimental results show that our method can achieve a 5.4% F-measure improvement over the traditional convolution tree kernel. © 2014 Association for Computational Linguistics. |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16572 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Sun, Le ,Han, Xianpei . A feature-enriched tree kernel for relation extraction[C]. Association for Computational Linguistics (ACL),2014:61-67. |
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