The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

Bidirectional Encoder Representations from Transformers (BERT) has gained increasing
attention from researchers and practitioners as it has proven to be an invaluable technique …

Sentiment analysis has become one of the most active research areas in natural language
processing, and the Arabic language retains its importance in this field. It is so because of …

Fake news has been around for a long time, but the rise of social networking applications
over recent years has rapidly increased the growth of fake news among individuals. The …

Text classification pertains to the automated procedure of assigning predefined labels or
categories to textual data. A comprehensive review of the existing literature on Arabic text …

The World Wide Web has revolutionized the way we live, causing the number of web pages
to increase exponentially. The web provides access to a tremendous amount of information …

The rapid progress in deep learning has propelled transformer-based models to the
forefront, establishing them as leading solutions for a multiple NLP tasks. These tasks span …

Artificial Intelligence techniques such as Machine Learning (ml) have not been exploited to
their maximum potential in the legal domain. This has been partially due to the insufficient …

Tokenization is an important early step in natural language processing (NLP) tasks. The
idea is to split the input sentence into smaller units, called tokens, for further processing …

Telehealth helps to facilitate access to medical professionals by enabling remote medical
services for the patients. These services have become gradually popular over the years with …