Papers with topic coherence measures

1 papers
Neural Topic Model with Reinforcement Learning (D19-1)

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Challenge: Experimental results show superior performance on perplexity and topic coherence measures compared to state-of-the-art topic models.
Approach: They propose to incorporate topic coherence measures as reward signals to guide the learning of a VAE-based topic model.
Outcome: The proposed model is able to separating background words dynamically from topic words eliminating the pre-processing step of filtering infrequent and/or top frequent words, typically required for learning traditional topic models.

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