Chinese Chunking Using ESVM-KNN

Author

Gao, Hong ; Huang, Degen ; Yang, Yuansheng ; Li, Lishuang

Author_Institution

Dept. of Comput. Sci. & Eng., Dalian Univ. of Technol.

Volume

1

fYear

2006

fDate

Nov. 2006

Firstpage

731

Lastpage

734

Abstract

This paper presents a method of Chinese text chunking based on editing support vector machine (ESVM) and K nearest neighbors (KNN). The word itself, part-of-speech (POS) tag, syllable and context information is extracted as the features of the vectors. The experimental results show that this model is efficient for Chinese text chunking. The hybrid machine learning model based on ESVM and KNN can achieve better results than SVM. The recall, precision and F-measure are up to 84.11%, 83.01% and 83.56% respectively in open test. And the combined ESVM-KNN model can be generalized to the fields of machine learning with unbalanced class distribution

Keywords

natural languages; support vector machines; text analysis; Chinese text chunking; ESVM-KNN; K-nearest neighbors; editing support vector machine; machine learning model; part-of-speech tag; Computer science; Data mining; Educational programs; Feature extraction; Machine learning; Nearest neighbor searches; Statistical learning; Support vector machine classification; Support vector machines; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2006 International Conference on

Conference_Location

Guangzhou

Print_ISBN

1-4244-0605-6

Electronic_ISBN

1-4244-0605-6

Type

conf

DOI

10.1109/ICCIAS.2006.294230

Filename

4072183