Hybrid Approach for Multi-Classification of News Documents Using Artificial Intelligence

Title

Hybrid Approach for Multi-Classification of News Documents Using Artificial Intelligence

Creator

Nagendra N.; Chandra J.

Description

In the context of news articles, text classification is essential for organizing and retrieving useful information from massive amounts of textual data. Effectively categorizing news titles has gotten more challenging due to the development of online news outlets and the ongoing production of news. A multi-text classification technique primarily targeted at news titles is shown. The suggested approach automates the classification of news titles into predetermined classes or subjects by combining deep learning approaches and natural language processing (NLP) algorithms. Data preprocessing, which includes text normalization, tokenization, and feature extraction, is the first step in the procedure. This prepares the raw news titles for deep learning models. 2024 IEEE.

Source

Proceedings - 2024 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024, pp. 466-473.

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

BERT; Deep Learning; Machine Learning; Natural Language Processing; Text Classification

Coverage

Nagendra N., Christ (Deemed to Be) University, Department of Computer Science., Bengaluru, India; Chandra J., Christ (Deemed to Be) University, Department of Computer Science., Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-835038564-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICICV62344.2024.00079

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193255348&doi=10.1109%2fICICV62344.2024.00079&partnerID=40&md5=b7e7cd69387a5bf8266796b9fd4c193d