Paper: Convolution Kernel over Packed Parse Forest

ACL ID P10-1090
Title Convolution Kernel over Packed Parse Forest
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010

This paper proposes a convolution forest ker- nel to effectively explore rich structured fea- tures embedded in a packed parse forest. As opposed to the convolution tree kernel, the proposed forest kernel does not have to com- mit 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 is- sues than the convolution tree kernel. The pa- per presents the formal definition of convolu- tion forest kernel and also illustrates the com- puting algorithm to fast compute the proposed convolution forest kernel. Experimental results on two NLP applications, relation extraction and semantic role labeling, show that the pro- posed ...