@inproceedings{679f2a12dd1b43cb9728a010488629be,
title = "Bangla News Classification Employing Deep Learning",
abstract = "In this paper, we have introduced a deep learning model for the classification of Bangla news articles as it is an important task for maintaining and managing Bangla news articles. The proposed model combines a hybrid Recurrent Neural Network (RNN) comprising Bi-directional Long-Short Term Memory (LSTM) and Bi-directional Gated Recurrent Unit (GRU) algorithms to improve classification accuracy. We tested the performance of proposed classifier with traditional machine learning techniques e.g. na{\"i}ve Bayes and decision tree induction. The experimental results indicate that the deep learning models achieved almost 90\% accuracy. This study provides valuable insights into the performance of various machine learning and deep learning techniques for Bangla news classification and highlights the potential of deep learning for this task.",
keywords = "Bangla News Classification, Deep Learning, Recurrent Neural Network",
author = "Siam, \{Abu Sayem Md\} and Hasan, \{Md Mehedi\} and Talukdar, \{Md Mushfikur\} and Arafat, \{Md Yeasir\} and Jobayer, \{Sayed Hossain\} and Farid, \{Dewan Md\}",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 1st International Conference on Intelligent Systems and Data Science, ISDS 2023 ; Conference date: 11-11-2023 Through 12-11-2023",
year = "2024",
doi = "10.1007/978-981-99-7649-2\_12",
language = "English",
isbn = "9789819976485",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "155--169",
editor = "Nguyen Thai-Nghe and Thanh-Nghi Do and Peter Haddawy",
booktitle = "Intelligent Systems and Data Science - 1st International Conference, ISDS 2023, Proceedings",
address = "Germany",
}