Determination of the Number of Topics Intrinsically: Is It Possible?
June 14, 2024 ยท Declared Dead ยท ๐ International Joint Conference on the Analysis of Images, Social Networks and Texts
"No code URL or promise found in abstract"
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Authors
Victor Bulatov, Vasiliy Alekseev, Konstantin Vorontsov
arXiv ID
2406.10402
Category
cs.CL: Computation & Language
Cross-listed
cs.IR,
math.PR
Citations
3
Venue
International Joint Conference on the Analysis of Images, Social Networks and Texts
Last Checked
5 months ago
Abstract
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.
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