Fake news stance detection using deep learning architecture (CNN-LSTM)
Society and individuals are negatively influenced both politically and socially by the
widespread increase of fake news either way generated by humans or machines. In the era …
widespread increase of fake news either way generated by humans or machines. In the era …
[PDF][PDF] The accuracy comparison among word2vec, glove, and fasttext towards convolution neural network (cnn) text classification
Feature extraction in the field of Text Processing or Natural Language Processing (NLP) has
its own challenges due to the characteristics of unstructured text. Thus, the selection of the …
its own challenges due to the characteristics of unstructured text. Thus, the selection of the …
Impact of convolutional neural network and FastText embedding on text classification
Efficient word representation techniques (word embeddings) with modern machine learning
models have shown reasonable improvement on automatic text classification tasks …
models have shown reasonable improvement on automatic text classification tasks …
COVINet: a convolutional neural network approach for predicting COVID-19 from chest X-ray images
COVID-19 pandemic is widely spreading over the entire world and has established
significant community spread. Fostering a prediction system can help prepare the officials to …
significant community spread. Fostering a prediction system can help prepare the officials to …
RFCNN: Traffic accident severity prediction based on decision level fusion of machine and deep learning model
Traffic accidents on highways are a leading cause of death despite the development of traffic
safety measures. The burden of casualties and damage caused by road accidents is very …
safety measures. The burden of casualties and damage caused by road accidents is very …
Misinformation detection using multitask learning with mutual learning for novelty detection and emotion recognition
Fake news or misinformation is the information or stories intentionally created to deceive or
mislead the readers. Nowadays, social media platforms have become the ripe grounds for …
mislead the readers. Nowadays, social media platforms have become the ripe grounds for …
What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion
One of the most time-critical challenges for the Natural Language Processing (NLP)
community is to combat the spread of fake news and misinformation. Existing approaches for …
community is to combat the spread of fake news and misinformation. Existing approaches for …
Fake news stance detection using selective features and FakeNET
The proliferation of fake news has severe effects on society and individuals on multiple
fronts. With fast-paced online content generation, has come the challenging problem of fake …
fronts. With fast-paced online content generation, has come the challenging problem of fake …
Automated disease diagnosis and precaution recommender system using supervised machine learning
Similar to many other professions, the medical field has undergone immense automation
during the past decade. The complexity and rise of healthcare data led to a surge in artificial …
during the past decade. The complexity and rise of healthcare data led to a surge in artificial …
Extensive hotel reviews classification using long short term memory
Reviews of users on social networks have been gaining rapidly interest on the usage of
sentiment analysis which serve as feedback to the government, public and private …
sentiment analysis which serve as feedback to the government, public and private …