Article

Uzbek News Categorization using Word Embeddings and Convolutional Neural Networks

Ilyos RabbimovFaculty of Applied Mathematics and Informatics, Samarkand State University, Samarkand, UzbekistanSami KobilovFaculty of Applied Mathematics and Informatics, Samarkand State University, Samarkand, UzbekistanIosif MporasSchool of Engineering and Computer Science, University of Hertfordshire, United Kingdom

2020en

ABI

Abstract

The rapid growth of online news belonging to different categories is causing users to spend a lot of time and effort searching for relevant and important news. Text categorization has a great significance in information retrieval and natural language processing where unstructured text can be organized into predefined categories. In this paper we investigate Uzbek news categorization using a convolution neural network and four word embedding models. We obtain two new word embeddings for Uzbek and present them in the Uzbek news categorization task.

Topics

Text and Document Classification Technologies Advanced Text Analysis Techniques Topic Modeling

Identifiers

DOI: 10.1109/aict50176.2020.9368822

Citations and references

Cited by 12 49 references

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