[HTML][HTML] Bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism for text sentiment classification
A Onan - Journal of King Saud University-Computer and …, 2022 - Elsevier
Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …
Deep neural network models, including convolutional neural networks (CNN) and recurrent …
Sentiment and context-aware hybrid DNN with attention for text sentiment classification
A tremendous amount of unstructured data, such as comments, opinions, and other sorts of
data is generated in real-time with the growth of web 2.0. Due to the unstructured nature of …
data is generated in real-time with the growth of web 2.0. Due to the unstructured nature of …
ABCDM: An attention-based bidirectional CNN-RNN deep model for sentiment analysis
Sentiment analysis has been a hot research topic in natural language processing and data
mining fields in the last decade. Recently, deep neural network (DNN) models are being …
mining fields in the last decade. Recently, deep neural network (DNN) models are being …
Combining attention-based bidirectional gated recurrent neural network and two-dimensional convolutional neural network for document-level sentiment classification
F Liu, J Zheng, L Zheng, C Chen - Neurocomputing, 2020 - Elsevier
Neural networks lately have achieved a great success on sentiment classification due to
their ability of feature extraction. However, it remains as an enormous challenge to model …
their ability of feature extraction. However, it remains as an enormous challenge to model …
KSCB: A novel unsupervised method for text sentiment analysis
In recent years, deep learning models (eg Convolutional Neural Networks (CNN) and Long
Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis …
Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis …
RoBERTa-LSTM: a hybrid model for sentiment analysis with transformer and recurrent neural network
Due to the rapid development of technology, social media has become more and more
common in human daily life. Social media is a platform for people to express their feelings …
common in human daily life. Social media is a platform for people to express their feelings …
Deep sentiments in roman urdu text using recurrent convolutional neural network model
Although over 64 million people worldwide speak Urdu language and are well aware of its
Roman script, limited research and efforts have been made to carry out sentiment analysis …
Roman script, limited research and efforts have been made to carry out sentiment analysis …
Attention-based sentiment analysis using convolutional and recurrent neural network
M Usama, B Ahmad, E Song, MS Hossain… - Future Generation …, 2020 - Elsevier
Convolution and recurrent neural network have obtained remarkable performance in natural
language processing (NLP). Moreover, from the attention mechanism perspective …
language processing (NLP). Moreover, from the attention mechanism perspective …
[HTML][HTML] Deep sentiment analysis using CNN-LSTM architecture of English and Roman Urdu text shared in social media
Sentiment analysis (SA) has been an active research subject in the domain of natural
language processing due to its important functions in interpreting people's perspectives and …
language processing due to its important functions in interpreting people's perspectives and …
LSTM with sentence representations for document-level sentiment classification
Recently, due to their ability to deal with sequences of different lengths, neural networks
have achieved a great success on sentiment classification. It is widely used on sentiment …
have achieved a great success on sentiment classification. It is widely used on sentiment …