Can Topic Modelling benefit from Word Sense Information?

LREC 2016 Adriana FerrugentoHugo Gon{\c{c}}alo OliveiraAna AlvesFilipe Rodrigues

This paper proposes a new topic model that exploits word sense information in order to discover less redundant and more informative topics. Word sense information is obtained from WordNet and the discovered topics are groups of synsets, instead of mere surface words... (read more)

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