Unsupervised Approaches for Computing Word Similarity in Portuguese

摘要

This paper presents several approaches for computing word similarity in Portuguese and is motivated by the recent availability of state-of-the-art distributional models of Portuguese words, which add to several lexical knowledge bases (LKBs) for this language, available for a longer time. The previous resources were exploited to answer word similarity tests, also recently available for Portuguese. We conclude that there are several valid approaches for this task, but not one that outperforms all the others in every single test. For instance, distributional models seem to capture relatedness better, but LKBs are better suited for computing genuine similarity.