An Unsupervised Approach to Word Sense Disambiguation Based on Hownet
Word Sense Disambigutaion is still considered one of the most challenging problemes in natural language processing .Ever since the fields inception ,WSD has been perceived as one of the central problems in NLP.This paper presents an unsupervised approach which is used as dictionary based on hownet and cilin,constructing context vector by means of secondorder context,clustering by k-means and disambiguates by calculating the similarity. Our experiments are based on the extraction of term and average accuracy is 85.13％ and 84.67％ for several ambiguous words in open test by this method.
word sense disambiguation Hownet second-order context clustering of k-means word sense
Chen Hao
Department of Computer Science Wuhan Bioengineering Institute Wuhan,China
国际会议
西安
英文
2026-2028
2011-12-23（万方平台首次上网日期，不代表论文的发表时间）