University of Hertfordshire

By the same authors

Uzbek News Categorization using Word Embeddings and Convolutional Neural Networks

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Original languageEnglish
Title of host publication2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) Proceedings
PublisherIEEE
Number of pages5
ISBN (Electronic)9781728173863
ISBN (Print)9781728173870
DOIs
Publication statusPublished - 9 Mar 2021
EventThe 14th IEEE International Conference on Application of Information and Communication Technologies - Tashkent, Uzbekistan
Duration: 7 Oct 2020 → 9 Oct 2020
http://www.aict.info/2020

Publication series

Name14th IEEE International Conference on Application of Information and Communication Technologies, AICT 2020 - Proceedings

Conference

ConferenceThe 14th IEEE International Conference on Application of Information and Communication Technologies
Abbreviated titleAICT 2020
Country/TerritoryUzbekistan
CityTashkent
Period7/10/20 → 9/10/20
Internet address

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.

Notes

© 2020 IEEE.

ID: 25186059