Topic Modeling in Embedding Spaces

Dieng Adji B.
Dieng Adji B.
Ruiz Francisco J. R.
Ruiz Francisco J. R.

Transactions of the Association for Computational Linguistics, pp. 439-453, 2019.

Cited by: 0|Bibtex|Views64|DOI:https://doi.org/10.1162/TACL_A_00325
Other Links: arxiv.org|academic.microsoft.com

Abstract:

Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics when working with large and heavy-tailed vocabularies. To ...

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