Stefanescu, Dan
Combining Knowledge and Corpus-based Measures for Word-to-Word Similarity
Stefanescu, Dan (University of Memphis) | Rus, Vasile (University of Memphis) | Niraula, Nobal Bikram (University of Memphis) | Banjade, Rajendra (University of Memphis)
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.