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Unsupervised Opinion Word Disambiguation Based on Topic Distribution Similarity
GUO Yingmei,SHI Xiaodong,CHEN Yidong,GAO Yan
Acta Scientiarum Naturalium Universitatis Pekinensis
The authors present an automatic method for choosing the correct sense of a polysemous word by using topic information, distance and mutual information of words. The only resources used in the method are an online dictionary and a web search engine. The sense of ambiguous opinion word can be broadly described from words in the context. Experiments show that new approach could achieve high accuracy, and especially keep superior performance for opinion words with more alternative senses.
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