no code implementations • 11 Mar 2020 • Faiza Memood, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Rehab Shehzadi, Muhammad Nabeel Asim
In order to accelerate the performance of various Natural Language Processing tasks for Roman Urdu, this paper for the very first time provides 3 neural word embeddings prepared using most widely used approaches namely Word2vec, FastText, and Glove.
no code implementations • 3 Mar 2020 • Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Sheraz Ahmad, Waqar Mahmood, Andreas Dengel
Second, it investigates the performance impact of traditional machine learning based Urdu text document classification methodologies by embedding 10 filter-based feature selection algorithms which have been widely used for other languages.