This paper investigates statistical and neural approaches for automatic text summarization and keyword extraction in the Uzbek language. Traditional techniques like TF-IDF and Non-negative Matrix Factorization (NMF) are applied for identifying key terms and latent topics. Additionally, deep...

The real-world application of Natural Language Processing (NLP) challenges for low-resource languages is growing rapidly. There has been a considerable deal of study using various ways to increase the quality of answers to these problems. This paper is devoted to automated inference from Uzbek...