Natural Language Processing (NLP) is an interdisciplinary field between linguistics and
computer science. Its main aim is to process natural (human) language using computer …

In the field of text classification, researchers have repeatedly shown the value of transformer-
based models such as Bidirectional Encoder Representation from Transformers (BERT) and …

We aim to highlight an interesting trend to contribute to the ongoing debate around
advances within legal Natural Language Processing. Recently, the focus for most legal text …

Automated legal text classification is a prominent research topic in the legal field. It lays the
foundation for building an intelligent legal system. Current literature focuses on international …

The Islamic jurisprudential legal system represents an essential component of the Islamic
religion, that governs many aspects of Muslims' daily lives. This creates many questions that …

Text classification has seen an increased use in both academic and industry settings.
Though rule based methods have been fairly successful, supervised machine learning has …

In order to provide benchmark performance for Urdu text document classification, the
contribution of this paper is manifold. First, it provides a publicly available benchmark …

With the increase in the number of Internet users, the amount of data has increased
dramatically. Millions of texts are written daily in most fields, whether cultural, scientific …

In current years, deep learning has showed promising results when used in the field of
natural language processing (NLP). Neural Networks (NNs) such as convolutional neural …

Abstract Natural Language Processing (NLP) and especially natural language text analysis
have seen great advances in recent times. Usage of deep learning in text processing has …