WikiRelate! computing semantic relatedness using wikipedia

AAAI(2006)

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摘要
Wikipedia provides a knowledge base for computing word relatedness in a more structured fashion than a search engine and with more coverage than WordNet. In this work we present experiments on using Wikipedia for computing semantic relatedness and compare it to WordNet on various benchmarking datasets. Existing relatedness measures perform better using Wikipedia than a baseline given by Google counts, and we show that Wikipedia outperforms WordNet when applied to the largest available dataset designed for that purpose. The best results on this dataset are obtained by integrating Google, WordNet and Wikipedia based measures. We also show that including Wikipedia improves the performance of an NLP application processing naturally occurring texts.
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关键词
present experiment,structured fashion,largest available dataset,knowledge base,best result,search engine,semantic relatedness,relatedness measure,word relatedness,nlp application processing,computational semantics
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