The grammatical function analysis between Korean adnoun clause and noun phrase by using support vector machines

Authors:
Songwook Lee;Tae-Yeoub Jang;Jungyun Seo
Affiliations:
Sogang University, Seoul, Korea;Hankuk University of Foreign Studies, Seoul, Korea;Sogang University, Seoul, Korea
Venue:
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Year:
2002

Citing 3
Cited 1

The nature of statistical learning theory

The nature of statistical learning theory
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features

ECML '98 Proceedings of the 10th European Conference on Machine Learning
Identifying syntactic role of antecedent in korean relative clause using corpus and thesaurus information

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2

Analysis of the grammatical functions between adnoun and noun phrases in Korean using Support Vector Machines

Natural Language Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

This study aims to improve the performance of identifying grammatical functions between an adnoun clause and a noun phrase in Korean. The key task is to determine the relation between the two constituents in terms of such functional categories as subject, object, adverbial, and appositive. The problem is mainly caused by the fact that functional morphemes, which are considered to be crucial for identifying the relation, are frequently omitted in the noun phrases. To tackle this problem, we propose to employ the Support Vector Machines(SVM) in determining the grammatical functions. Through an experiment with a tagged corpus for training SVMs, the proposed model is found to be useful.