The human language is cryptic since words can be interpreted differently based upon the context within which they occur. The exact meaning of a particular word in its context might be trivial for humans who are generally ...

In many Sub-Saharan countries, the advancement of public transport is frequently overshadowed by more prioritised sectors, highlighting the need for innovative approaches to enhance both the Quality of Service (QoS) and ...

Social media creates an echo chamber effect that is closely related to social movement theory, which aims to mobilise people to change society. In South Africa, there has been an increase in protests that appear to have ...

Continual learning is the sequential learning of different tasks by a machine learning model. Continual learning is known to be hindered by catastrophic interference or forgetting, i.e. rapid unlearning of earlier learned ...

The interpretability of models has been one of the focal research topics in the machine learning community due to a rise in the use of black box models and complex state-of-the-art models [6]. Most of these models are ...

It was researched whether a multilingual Bantu pretraining corpus could be created from freely available data. Here, to create the dataset, Bantu text extracted from datasets that are freely available online (mainly from ...

The elections in South Africa are contested by multiple political parties appealing to a diverse population that comes from a variety of socioeconomic backgrounds. As a result, a rich source of discourse is created to ...

Nonstationary data with concept drift occurring is usually made up of different underlying data generating processes. Therefore, if the knowledge of the existence of different segments in the dataset is not taken into ...

Healthcare fraud is considered a challenge for many societies. Healthcare funding that could be spent on medicine, care for the elderly or emergency room visits is instead lost to fraudulent activities by medical practitioners ...

Recurrent Neural Networks (RNNs) are variants of Neural Networks that are able to learn temporal relationships between sequences presented to the neural network. RNNs are often employed to learn underlying relationships ...