International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 11, No. 6, 8 Dec. 2021
Cover page and Table of Contents: PDF (size: 785KB)
Author(s)
Amran Hossain
1,*
Niraj Chaudhary
1
Zahid Hasan Rifad
1
B M Mainul Hossain
1
Index Terms
Categorization, Bangla news headlines, neural networks, LSTM, GRU.
Abstract
News categorization from various newspapers is important as readers want to read the news by category. But, the readers face difficulty if the news from different categories is presented without any order. This study aims to determine the category of news from online Bangla newspapers. In this context Bangla news headlines data, along with its categories, were collected from various online newspapers through scrapping. Eight categories of news are considered for this work and the headlines of the news are used for categorization. The input data is modeled by the LSTM and GRU neural networks, and the predicted category is compared with the actual category. For LSTM model, the result gives an accuracy of 82.74% and GRU model, The result gives an accuracy of 87.48%. GRU accuracy is higher than LSTM.
Because, GRU training performance is faster than that of LSTM. In GRU 64 units used and in LSTM 128 units used for this research. For this reason, it also suggests that the GRU model gives better results than that of LSTM.
Cite This Paper
Amran Hossain, Niraj Chaudhary, Zahid Hasan Rifad, B M Mainul Hossain, " Bangla News Headline Categorization", International Journal of Education and Management Engineering (IJEME), Vol.11, No.6, pp. 39-48, 2021. DOI: 10.5815/ijeme.2021.06.05
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