A Hybrid KAN-BiLSTM Transformer with Multi-Domain Dynamic Attention Model for Cybersecurity
With the exponential growth of cyberbullying cases on social media, there is a growing need to develop effective mechanisms for its detection and prediction, which can create a safer and more comfortable digital environment. One of the areas with such potential is the application of natural language...
Saved in:
| Main Authors: | Aleksandr Chechkin, Ekaterina Pleshakova, Sergey Gataullin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Technologies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7080/13/6/223 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid CNN–BiLSTM–DNN Approach for Detecting Cybersecurity Threats in IoT Networks
by: Bright Agbor Agbor, et al.
Published: (2025-02-01) -
Prediction Method of Tangerine Peel Drying Moisture Ratio Based on KAN-BiLSTM and Multimodal Feature Fusion
by: Qi Ren, et al.
Published: (2025-05-01) -
Predicting depression risk in middle-aged and elderly adults in China using CNN-BiLSTM-Attention mechanism and LSTM+SHAP framework
by: Shengxian Bi, et al.
Published: (2025-08-01) -
Research on Chinese predicate head recognition based on Highway-BiLSTM network
by: Ruizhang HUANG, et al.
Published: (2021-01-01) -
Monthly Precipitation Prediction Based on Attention-BiLSTM Model
by: CHENG Yuxiang, et al.
Published: (2024-06-01)