An Unsupervised Approach to Word Sense Disambiguation Based on HowNet
Ji Donghong · Zhongwen xinxi xuebao · 2005
An unsupervised WSD(word sense disambiguation) can avoid big labor cost and it is possible to adjust to deal with large-scale ,so WSD has extensive applications in many fields. This paper presents an unsupervised approach which constructs context vector by means of second-order context, clustering by k-means and disambiguates by calculating the similarity. Our experiments are based on the extraction of term and average accuracy is 82.62% and 80.87% for 8 ambiguous words in open test by this method.