Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

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Interactive AI-Powered Real-Time News Fetching and Classification System Using BERT-Based Models

Authors
K. Venkatesh Guru1, *, J. Nirmala Gandhi2, A. Rajiv Kannan3, K. Mohan4, S. Ranjith4, K. Mithun4
1Associate Professor, Computer Science and Engineering, KSR College of Engineering, Tiruchengode, Namakkal, Tamil Nadu, India
2Assistant Professor, Computer Science and Engineering, KSR College of Engineering, Tiruchengode, Namakkal, Tamil Nadu, India
3Professor, Computer Science and Engineering, KSR College of Engineering, Tiruchengode, Namakkal, Tamil Nadu, India
4Student, Computer Science and Engineering, KSR College of Engineering, Tiruchengode, Namakkal, Tamil Nadu, India
*Corresponding author. Email: venkateshguruk@gmail.com
Corresponding Author
K. Venkatesh Guru
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_67How to use a DOI?
Keywords
Real-Time News Classification; BERT; AI-Powered Systems; Natural Language Processing; Interactive Systems; Sentiment Analysis; Fake News Detection; Ethical AI; Multilingual Processing; Performance Metrics
Abstract

Provable approach of real time news fetching and classification systems has developed with the progress of Natural Language processing (NLP) particularly after early 2023. The high accuracy, efficiency and interactivity gained with the help of AI-driven systems like those based on BERT models for news categorization are discussed in this paper. The conducted analyses rely on specific data acquisition for targeted applications, and controlled evaluation environments to enable comparative use of BERT across different tasks such as sentiment analysis, fake news detection, and domain-specific classifications such as classifying financial and political news. The studies highlight the need for user-centric designs, a focus on performance metrics, and the groundwork for real-time processing capabilities. Moreover, datasets being carefully curated and final products being high quality also address for ethical challenges like fake news and other biases. These contributions lay the groundwork for future studies on multilingual and real-world news classification systems.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_67How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - K. Venkatesh Guru
AU  - J. Nirmala Gandhi
AU  - A. Rajiv Kannan
AU  - K. Mohan
AU  - S. Ranjith
AU  - K. Mithun
PY  - 2025
DA  - 2025/05/23
TI  - Interactive AI-Powered Real-Time News Fetching and Classification System Using BERT-Based Models
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 779
EP  - 794
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_67
DO  - 10.2991/978-94-6463-718-2_67
ID  - Guru2025
ER  -