WordNet-based similarity metrics for adjectives
Emiel van Miltenburg · 2016
Le and Fokkens (2015) recently showed that taxonomy-based approaches are more reliable than corpus-based approaches in estimating human similarity ratings.On the other hand, distributional models provide much better coverage.The lack of an established similarity metric for adjectives in WordNet is a case in point.I present initial work to establish such a metric, and propose ways to move forward by looking at extensions to WordNet.I show that the shortest path distance between derivationally related forms provides a reliable estimate of adjective similarity.Furthermore, I find that a hybrid method combining this measure with vector-based similarity estimations gives us the best of both worlds: more reliable similarity estimations than vectors alone, but with the same coverage as corpus-based methods.