The information age has been a critical driver in the impressive advancement of Natural Language Processing (NLP) applications in recent years. The benefits of these applications have been prominent in populations with ...

Understanding public sentiment is vital for political parties in order for them to be able to structure their election campaigns around voter expectations. The study focuses on unsupervised learning to assess the variation ...

The judicial system is the central pillar of law and order across the world. It is re- sponsible for maintaining order amongst citizens and also solving litigations that arise. Although this system has worked quite well, ...

The schedulability analysis of real-time systems is challenged by the state space complexity of such systems. It is difficult to develop concrete state space models that can be used to verify the schedulability of real-time ...

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 ...

In recent years, there has been an increasing development of hyper-heuristics in the field of combinatorial optimisation. Broadly speaking, the term hyper-heuristic refers to a technique or algorithm that aims to provide ...

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 ...