2026-10-24T07:14:38Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4596 2022-03-24T23:12:44Z 1582963302567:1597824273898 user-ucsy

A Study on a Joint Deep Learning Model for Myanmar Text Classification Phyu, Myat Sapal Nwet, Khin Thandar Text classification is one of the most criticalareas of research in the field of natural languageprocessing (NLP). Recently, most of the NLP tasksachieve remarkable performance by using deeplearning models. Generally, deep learning modelsrequire a huge amount of data to be utilized. Thispaper uses pre-trained word vectors to handle theresource-demanding problem and studies theeffectiveness of a joint Convolutional Neural Networkand Long Short Term Memory (CNN-LSTM) forMyanmar text classification. The comparativeanalysis is performed on the baseline ConvolutionalNeural Networks (CNN), Recurrent Neural Networks(RNN) and their combined model CNN-RNN. 2020-02-28 http://hdl.handle.net/20.500.12678/0000004596 https://meral.edu.mm/records/4596