Advanced
A Study on Optimization of Support Vector Machine Classifier for Word Sense Disambiguation
A Study on Optimization of Support Vector Machine Classifier for Word Sense Disambiguation
Journal of Information Management. 2011. Apr, 42(2): 193-210
  • Published : April 30, 2011
Download
PDF
Export by style
Article
Author
Metrics
Cited by
About the Authors
Lee, Yong-Gu

Abstract
The study was applied to context window sizes and weighting method to obtain the best performance of word sense disambiguation using support vector machine. The context window sizes were used to a 3-word, sentence, 50-bytes, and document window around the targeted word. The weighting methods were used to Binary, Term Frequency(TF), TF ${\times}$ Inverse Document Frequency(IDF), and Log TF ${\times}$ IDF. As a result, the performance of 50-bytes in the context window size was best. The Binary weighting method showed the best performance.
Keywords
References