Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.
- DOI
- 10.1007/s00180-022-01246-z
- Published
- 2023
- Container
- Computational statistics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s00180-022-01246-z,
title = {Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.},
author = {Weisser C and Gerloff C and Thielmann A and Python A and Reuter A and Kneib T and Säfken B},
year = {2023},
journal = {Computational statistics},
doi = {10.1007/s00180-022-01246-z},
url = {https://doi.org/10.1007/s00180-022-01246-z}
}RIS
TY - JOUR TI - Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data. AU - Weisser C AU - Gerloff C AU - Thielmann A AU - Python A AU - Reuter A AU - Kneib T AU - Säfken B PY - 2023 JO - Computational statistics DO - 10.1007/s00180-022-01246-z UR - https://doi.org/10.1007/s00180-022-01246-z ER -
APA
C, W., C, G., A, T., A, P., A, R., T, K., & B, S. (2023). Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.. Computational statistics. https://doi.org/10.1007/s00180-022-01246-z
Source records
- pubmed · retrieved 2026-09-25T21:49:12.423Z