An Automated News Text Classification Information System
Main Article Content
Abstract
An information system for the categorization of news texts using machine learning algorithms is being planned and developed in this project. An online platform and an automated categorization system make up the data system in question. We have preprocessed the text data. In order to train classifiers using the grid search method, many experiments were carried out. We have tested four different categorization algorithms: naïve Bayesian, logistic regression, random forest, and artificial neural network. Several measures, including F-score, recall, and precision, have been used to assess the trained classifiers' classification quality. An additional goal in developing the website was to provide easy access to the information system.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
References
C. D. Manning, P. Raghavan and H. Schütze, "Introduction to Information Retrieval," in Cambridge: Cambridge University Press, 2008.
Show in Context CrossRef Google Scholar
A. G. Shagraev, "Modification development and implementation of methods for classifying news texts," in Cand. tech. sci. diss., Moscow: MPEI Publ., 2014.
Show in Context Google Scholar
K. A. Yakil and N. Yu. Ryazanova, "SMS spam filtering", Automation. Modern technologies, vol. #9, pp. 19-24, 2016.
Show in Context Google Scholar
A. M. Tsytulsky, A. V. Ivannikov and I. S. Rogov, "NLP: processing of natural languages", StudNet, vol. 3, no. 6, pp. 467-475, 2020.
Show in Context Google Scholar
O. Harmatiy, "Features of news materials texts of news agencies", IV International Scientific and Practical Conference Stylistics: language speech and text, February 2017.