Papers by Felipe Viegas

1 papers
CluHTM - Semantic Hierarchical Topic Modeling based on CluWords (2020.acl-main)

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Challenge: Hierarchical Topic modeling (HTM) exploits latent topics and relationships among them as a powerful tool for data analysis and exploration.
Approach: They propose a hierarchical matrix factorization that exploits latent topics and relationships among them to create a powerful tool for data analysis and exploration.
Outcome: The proposed method outperforms baselines and datasets in the vast majority of cases.

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