Hybrid Approach for Multi-Classification of News Documents Using Artificial Intelligence
BERT; Deep Learning; Machine Learning; Natural Language Processing; Text Classification
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.
Proceedings - 2024 5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024, pp. 466-473.
Institute of Electrical and Electronics Engineers Inc.
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
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