Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.10402 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910546445467648 |
|---|---|
| author | Bulatov, Victor Alekseev, Vasiliy Vorontsov, Konstantin |
| author_facet | Bulatov, Victor Alekseev, Vasiliy Vorontsov, Konstantin |
| contents | The number of topics might be the most important parameter of a topic model. The topic modelling community has developed a set of various procedures to estimate the number of topics in a dataset, but there has not yet been a sufficiently complete comparison of existing practices. This study attempts to partially fill this gap by investigating the performance of various methods applied to several topic models on a number of publicly available corpora. Further analysis demonstrates that intrinsic methods are far from being reliable and accurate tools. The number of topics is shown to be a method- and a model-dependent quantity, as opposed to being an absolute property of a particular corpus. We conclude that other methods for dealing with this problem should be developed and suggest some promising directions for further research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_10402 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Determination of the Number of Topics Intrinsically: Is It Possible? Bulatov, Victor Alekseev, Vasiliy Vorontsov, Konstantin Computation and Language Information Retrieval Probability The number of topics might be the most important parameter of a topic model. The topic modelling community has developed a set of various procedures to estimate the number of topics in a dataset, but there has not yet been a sufficiently complete comparison of existing practices. This study attempts to partially fill this gap by investigating the performance of various methods applied to several topic models on a number of publicly available corpora. Further analysis demonstrates that intrinsic methods are far from being reliable and accurate tools. The number of topics is shown to be a method- and a model-dependent quantity, as opposed to being an absolute property of a particular corpus. We conclude that other methods for dealing with this problem should be developed and suggest some promising directions for further research. |
| title | Determination of the Number of Topics Intrinsically: Is It Possible? |
| topic | Computation and Language Information Retrieval Probability |
| url | https://arxiv.org/abs/2406.10402 |