Systematic reviews in sentiment analysis: a tertiary study
A Ligthart, C Catal, B Tekinerdogan - Artificial Intelligence Review, 2021 - Springer
With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …
on the web that provides opinions of people on different subjects. Sentiment analysis is the …
A survey on aspect-based sentiment classification
G Brauwers, F Frasincar - ACM Computing Surveys, 2022 - dl.acm.org
With the constantly growing number of reviews and other sentiment-bearing texts on the
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …
Automatic modulation classification using CNN-LSTM based dual-stream structure
Z Zhang, H Luo, C Wang, C Gan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Deep learning (DL) has recently aroused substantial concern due to its successful
implementations in many fields. Currently, there are few studies on the applications of DL in …
implementations in many fields. Currently, there are few studies on the applications of DL in …
Attention-emotion-enhanced convolutional LSTM for sentiment analysis
Long short-term memory (LSTM) neural networks and attention mechanism have been
widely used in sentiment representation learning and detection of texts. However, most of …
widely used in sentiment representation learning and detection of texts. However, most of …
A novel method based on deep transfer unsupervised learning network for bearing fault diagnosis under variable working condition of unequal quantity
H Su, X Yang, L Xiang, A Hu, Y Xu - Knowledge-based systems, 2022 - Elsevier
Recently, intelligent fault recognition means have been progressed rapidly and have
attained marvelous achievement. Most of them have an assumption where those source and …
attained marvelous achievement. Most of them have an assumption where those source and …
Human action recognition using convolutional LSTM and fully-connected LSTM with different attentions
This paper aims to address the human action recognition issue by using convolutional long
short-term memory networks (Conv-LSTM) and fully-connected LSTM (FC-LSTM) with …
short-term memory networks (Conv-LSTM) and fully-connected LSTM (FC-LSTM) with …
Scalable multi-channel dilated CNN–BiLSTM model with attention mechanism for Chinese textual sentiment analysis
C Gan, Q Feng, Z Zhang - Future Generation Computer Systems, 2021 - Elsevier
Due to the complex semantics of natural language, the multi-sentiment polarity of words, and
the long-dependence of sentiments between words, the existing sentiment analysis methods …
the long-dependence of sentiments between words, the existing sentiment analysis methods …
An attention-based CNN-LSTM model for subjectivity detection in opinion-mining
Opinion-mining generally refers to analyzing opinions on various topics available in the form
of text. It is an essential operation of natural language processing since it enables efficient …
of text. It is an essential operation of natural language processing since it enables efficient …
Deep learning approach for aspect-based sentiment classification: a comparative review
KW Trisna, HJ Jie - Applied Artificial Intelligence, 2022 - Taylor & Francis
The emergence of various e-commerce sites has led to an increase in review sites for
various services and products. People nowadays easily get information about products and …
various services and products. People nowadays easily get information about products and …
Social media sentiment analysis through parallel dilated convolutional neural network for smart city applications
Deep Learning is considered to leverage smart cities through social media sentiment
analysis. The digital content in social media can be used for many smart city applications …
analysis. The digital content in social media can be used for many smart city applications …