Skip to main navigation
Skip to search
Skip to main content
University of Portsmouth Home
Help & FAQ
Link opens in a new tab
Search content at University of Portsmouth
Home
Profiles
Organisations
Research outputs
Student theses
Datasets
Projects
Activities
Prizes
Press/Media
Equipment
A proposed ensemble voting model for fake news detection
Sherry Girgis
,
Eslam Amer
NetSync
Misr International University
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A proposed ensemble voting model for fake news detection'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
INIS
algorithms
100%
datasets
100%
neural networks
100%
detection
100%
learning
50%
processing
50%
units
50%
information
50%
evaluation
50%
accuracy
50%
performance
50%
machine learning
50%
hybrids
50%
forests
50%
randomness
50%
public opinion
50%
natural language
50%
Computer Science
Random Decision Forest
100%
Convolutional Neural Network
100%
Recurrent Neural Network
100%
Deep Learning Method
100%
Natural Language Processing
100%
Machine Learning
100%
Learning System
100%
Extracted Feature
100%
Gated Recurrent Unit
100%
Fake News Detection
100%