# Uzbek text's correspondence with the educational potential of pupils: a case study of the School corpus

arXiv: https://arxiv.org/abs/2303.00465 · HTML: https://mlsanity.com/paper/2303.00465/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 23 references that are in the map.
- First posted on arXiv 1 Mar 2023.

## Builds on (most cited first, 5 of 5)

- [Representation learning for very short texts using weighted word embedding aggregation](https://mlsanity.com/paper/1607.00570/) (2016)
- [SimRelUz: Similarity and Relatedness scores as a Semantic Evaluation dataset for Uzbek language](https://mlsanity.com/paper/2205.06072/) (2022)
- [A machine transliteration tool between Uzbek alphabets](https://mlsanity.com/paper/2205.09578/) (2022)
- [Development of a rule-based lemmatization algorithm through Finite State Machine for Uzbek language](https://mlsanity.com/paper/2210.16006/) (2022)
- [Accuracy of the Uzbek stop words detection: a case study on "School corpus"](https://mlsanity.com/paper/2209.07053/) (2022)

## Abstract (arXiv)

One of the major challenges of an educational system is choosing appropriate content considering pupils' age and intellectual potential. In this article the experiment of primary school grades (from 1st to 4th grades) is considered for automatically determining the correspondence of an educational materials recommended for pupils by using the School corpus where it includes the dataset of 25 school textbooks confirmed by the Ministry of preschool and school education of the Republic of Uzbekistan. In this case, TF-IDF scores of the texts are determined, they are converted into a vector representation, and the given educational materials are compared with the corresponding class of the School corpus using the cosine similarity algorithm. Based on the results of the calculation, it is determined whether the given educational material is appropriate or not appropriate for the pupils' educational potential.