Determination of the Number of Topics Intrinsically: Is It Possible?
<|reference_start|>Determination of the Number of Topics Intrinsically: Is It Possible?: 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.<|reference_end|>
@article{bulatov2024determination,
    title={Determination of the Number of Topics Intrinsically: Is It Possible?},
    author={Victor Bulatov, Vasiliy Alekseev, Konstantin Vorontsov},
    journal={Recent Trends in Analysis of Images, Social Networks and Texts.
  AIST 2023. Communications in Computer and Information Science, vol 1905.
  Springer, Cham},
    year={2024},
    doi={10.1007/978-3-031-67008-4_1},
    archivePrefix={arXiv},
    eprint={2406.10402},
    primaryClass={cs.CL cs.IR math.PR}
}