2001 ChunkingWithSVMs

• (Kudo & Matsumoto, 2001) ⇒ Taku Kudo, Yuji Matsumoto. (2001). “Chunking with Support Vector Machines" In: Proceedings of NAACL Conference (NAACL 2001).

Subject Headings: BaseNP Chunking Algorithm, SVM.

Notes

• It had achieved the highest performance by 2002 on the RM95 Chunking Benchmark Task.
  • P=94.15%, R=94.29%, F=94.22

Cited By

~396 http://scholar.google.com/scholar?cites=14400800018354132323 -

Quotes

Abstract

• We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimensional feature spaces. Furthermore, by the Kernel principle, SVMs can carry out training with smaller computational overhead independent of their dimensionality. We apply weighted voting of 8 SVMs-based systems trained with distinct chunk representations. Experimental results show that our approach achieves higher accuracy than previous approaches.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2001 ChunkingWithSVMs	Taku Kudo Yuji Matsumoto			Chunking with Support Vector Machines		Proceedings of NAACL Conference	http://cactus.aist-nara.ac.jp/~taku-ku/publications/naacl2001.pdf			2001