Like most natural language disambiguation tasks, word sense disambiguation (WSD) requires world knowledge for accurate predictions. Several proxies for this knowledge have been in...
We present a corpus{based approach to word{sense disambiguation that only requires information that can be automatically extracted from untagged text. We use unsupervised techniqu...
This paper revisits the one sense per collocation hypothesis using fine-grained sense distinctions and two different corpora. We show that the hypothesis is weaker for fine-graine...
Previous algorithms to compute lexical chains suffer either from a lack of accuracy in word sense disambiguation (WSD) or from computational inefficiency. In this paper, we presen...
In this paper, we proposed a new supervised word sense disambiguation (WSD) method based on a pairwise alignment technique, which is used generally to measure a similarity between...