2006 TreeKernelEngineeringForPropositionReranking

• (Moschitti et al., 2006) ⇒ Alessandro Moschitti, Daniele Pighin, Roberto Basili. (2006). “Tree Kernel Engineering for Proposition Re-ranking.” In: Proceedings of ECML/PKDD 2006 Workshop on Mining and Learning with Graphs (MLG 2006).

Subject Headings: Tree Kernel Function, Semantic Role Labeling Task

Quotes

Abstract

Recent work on the design of automatic systems for semantic role labeling has shown that such task is complex from both modeling and implementation point of views. Tree kernels alleviate such complexity as kernel functions generate features automatically and require less software development for data pre-processing. In this paper, we study several tree kernel approaches for boundary detection, argument classification and, most notably, proposition re-ranking. The comparative experiments on Support Vector Machines with such kernels on the CoNLL 2005 dataset show that very simple tree manipulations trigger automatic feature engineering that highly improves accuracy and efficiency in every SRL phase.

References

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• 7. Alessandro Moschitti, B. Coppola, D. Pighin, Roberto Basili. (2005). “Engineering of Syntactic Features for Shallow Semantic Parsing.” In: Proceedings of the ACL 2005 Workshop on Feature Engineering for Machine Learning in Natural Language Processing. (2005)
• 8. Alessandro Moschitti, D. Pighin, and Roberto Basili. (2006). “Tree Kernel Engineering in Semantic Role Labeling Systems.” In: Proceedings of the EACL 2006 Workshop on Learning Structured Information in Natural Language Applications. (2006)

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2006 TreeKernelEngineeringForPropositionReranking	Roberto Basili Alessandro Moschitti Daniele Pighin			Tree Kernel Engineering for Proposition Re-ranking			http://www.inf.uni-konstanz.de/mlg2006/17.pdf