Topic Modeling in Embedding Spaces
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 this end, we develop the embedded topic model (etm), a generative model of docume...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2020-07-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://www.mitpressjournals.org/doi/abs/10.1162/tacl_a_00325 |