More is not always better: balancing sense distributions for all-words Word Sense Disambiguation

COLING 2016 Marten PostmaRuben Izquierdo BeviaPiek Vossen

Current Word Sense Disambiguation systems show an extremely poor performance on low frequent senses, which is mainly caused by the difference in sense distributions between training and test data. The main focus in tackling this problem has been on acquiring more data or selecting a single predominant sense and not necessarily on the meta properties of the data itself... (read more)

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