AAAI Publications, The Twenty-Seventh International Flairs Conference

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Combining Knowledge and Corpus-based Measures for Word-to-Word Similarity
Dan Stefanescu, Vasile Rus, Nobal Bikram Niraula, Rajendra Banjade

Last modified: 2014-05-03

Abstract


This paper shows that the combination of knowledge and corpus-based word-to-word similarity measures can produce higher agreement with human judgment than any of the in-dividual measures. While this might be a predictable result, the paper provides insights about the circumstances under which a combination is productive and about the improve-ment levels that are to be expected. The experiments presented here were conducted using the word-to-word similarity measures included in SEMILAR, a freely available semantic similarity toolkit.

Keywords


word-to-word similarity; Latent Semantic Analysis; semantic models

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