Network intrusion detection combined hybrid sampling with deep hierarchical network
K Jiang, W Wang, A Wang, H Wu - IEEE access, 2020 - ieeexplore.ieee.org
Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …
and preventing malicious activities. Due to the complex and time-varying network …
Traffic accident detection and condition analysis based on social networking data
Accurate detection of traffic accidents as well as condition analysis are essential to
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
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 …
User reviews: Sentiment analysis using lexicon integrated two-channel CNN–LSTM family models
Sentiment analysis, which refers to the task of detecting whether a textual item (eg, a product
review and a blog post) expresses a positive or negative opinion in general or about a given …
review and a blog post) expresses a positive or negative opinion in general or about a given …
An LSTM short-term solar irradiance forecasting under complicated weather conditions
Y Yu, J Cao, J Zhu - IEEE Access, 2019 - ieeexplore.ieee.org
Complicated weather conditions lead to intermittent, random and volatility in photovoltaic
(PV) systems, which makes PV predictions difficult. A recurrent neural network (RNN) is …
(PV) systems, which makes PV predictions difficult. A recurrent neural network (RNN) is …
BERT: A sentiment analysis odyssey
S Alaparthi, M Mishra - Journal of Marketing Analytics, 2021 - Springer
The study investigates relative effectiveness of four sentiment analysis techniques:(1)
unsupervised lexicon-based model using SentiWordNet,(2) traditional supervised machine …
unsupervised lexicon-based model using SentiWordNet,(2) traditional supervised machine …
Attention-based LSTM network for rotatory machine remaining useful life prediction
H Zhang, Q Zhang, S Shao, T Niu, X Yang - Ieee Access, 2020 - ieeexplore.ieee.org
As one of the key components in mechanical systems, rotatory machine plays a significant
role in safe and stable operation. Accurate prediction of the Remaining Useful Life (RUL) of …
role in safe and stable operation. Accurate prediction of the Remaining Useful Life (RUL) of …
Exploration of social media for sentiment analysis using deep learning
LC Chen, CM Lee, MY Chen - Soft Computing, 2020 - Springer
With the rapid growth of web content from social media, such studies as online opinion
mining or sentiment analysis of text have started receiving attention from government …
mining or sentiment analysis of text have started receiving attention from government …
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 …
A novel deep learning-based sentiment analysis method enhanced with emojis in microblog social networks
X Li, J Zhang, Y Du, J Zhu, Y Fan… - Enterprise Information …, 2023 - Taylor & Francis
To exactly classify sentiments of microblog reviews with emojis in microblog social networks,
this paper first proposes an emoji vectorisation method to achieve emoji vectors. Then, an …
this paper first proposes an emoji vectorisation method to achieve emoji vectors. Then, an …