@inproceedings{8355800fa89a4307b310ac1eba86c9b0,
title = "Convolution kernel over packed parse forest",
abstract = "This paper proposes a convolution forest kernel to effectively explore rich structured features embedded in a packed parse forest. As opposed to the convolution tree kernel, the proposed forest kernel does not have to commit to a single best parse tree, is thus able to explore very large object spaces and much more structured features embedded in a forest. This makes the proposed kernel more robust against parsing errors and data sparseness issues than the convolution tree kernel. The paper presents the formal definition of convolution forest kernel and also illustrates the computing algorithm to fast compute the proposed convolution forest kernel. Experimental results on two NLP applications, relation extraction and semantic role labeling, show that the proposed forest kernel significantly outperforms the baseline of the convolution tree kernel.",
author = "Min Zhang and Hui Zhang and Haizhou Li",
note = "Publisher Copyright: {\textcopyright} 2010 Association for Computational Linguistics.; 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 ; Conference date: 11-07-2010 Through 16-07-2010",
year = "2010",
language = "英语",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "875--885",
editor = "Jan Hajic and Sandra Carberry and Stephen Clark",
booktitle = "ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Conference Proceedings",
address = "澳大利亚",
}