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BERTopic: Neural topic modeling with a class-based TF-IDF procedure
Maarten Grootendorst, 2022. arXiv.
BERTopic, a topic-modelling method that clusters document embeddings from a transformer and names each cluster with a class-based TF-IDF.
What it's used for here
The inductive-methods survey lists it among topic models to try on the manuscript's pages.
Cited by on this site 1 record
1 methods surveys
SRCInductive methods
Cite it
Grootendorst, M. (2022). BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv. https://arxiv.org/abs/2203.05794
@article{grootendorst2022bertopic,
author = {Grootendorst, Maarten},
title = {BERTopic: Neural topic modeling with a class-based TF-IDF procedure},
journal = {arXiv},
year = {2022},
url = {https://arxiv.org/abs/2203.05794}
}TY - GEN TI - BERTopic: Neural topic modeling with a class-based TF-IDF procedure AU - Grootendorst, Maarten PY - 2022 JO - arXiv UR - https://arxiv.org/abs/2203.05794 ER -
Grootendorst, Maarten. “BERTopic: Neural topic modeling with a class-based TF-IDF procedure.” arXiv (2022).