# Formal concept analysis for evaluating intrinsic dimension of a natural language

arXiv: https://arxiv.org/abs/2311.10862 · HTML: https://mlsanity.com/paper/2311.10862/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 25 references that are in the map.
- First posted on arXiv 17 Nov 2023.

## Builds on (most cited first, 1 of 1)

- [Intrinsic Dimension of Geometric Data Sets](https://mlsanity.com/paper/1801.07985/) (2018)

## Built on by (most cited first, 1 of 1)

- [What is the textitintrinsic dimension of your binary data? -- and how to compute it quickly](https://mlsanity.com/paper/2404.06326/) (2024)

## Abstract (arXiv)

Some results of a computational experiment for determining the intrinsic dimension of linguistic varieties for the Bengali and Russian languages are presented. At the same time, both sets of words and sets of bigrams in these languages were considered separately. The method used to solve this problem was based on formal concept analysis algorithms. It was found that the intrinsic dimensions of these languages are significantly less than the dimensions used in popular neural network models in natural language processing.