Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a semi-supervised technique for word sense disambiguation that exploits external knowledge acquired in an unsupervised manner. In particular,  use a combination of basic kernel functions to independently estimate syntagmatic and domain similarity, building a set of word-expert classifiers that share a common domain model acquired from a large corpus of unlabeled data. The results show that the proposed approach achieves state-of-the-art performance on a wide range of lexical sample tasks and on the English all-words task of Senseval-3, although it uses a considerably smaller number of training examples than other methods.
['Claudio Giuliano', 'Alfio Massimiliano Gliozzo', 'Carlo Strapparava']
I am writing a research paper on a idea Kernel methods for minimally supervised wsd
[{"from": "human", "value": "I am writing a research paper on a idea Kernel methods for minimally supervised wsd"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a semi-supervised technique for word sense disambiguation that exploits external knowledge acquired in an unsupervised manner. In particular,  use a combination of basic kernel functions to independently estimate syntagmatic and domain similarity, building a set of word-expert classifiers that share a common domain model acquired from a large corpus of unlabeled data. The results show that the proposed approach achieves state-of-the-art performance on a wide range of lexical sample tasks and on the English all-words task of Senseval-3, although it uses a considerably smaller number of training examples than other methods."}]