In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

The process of creating high-quality labeled data is crucial for training machine-learning
models, but it can be a time-consuming and labor-intensive process. Moreover, manual …

Over the last decade Deep learning-based models surpasses classical machine learning
models in a variety of text classification tasks. The primary challenge with text classification …

Sentiment analysis, commonly known as “opinion mining,” aims to identify sentiment
polarities in opinion texts. Recent years have seen a significant increase in the acceptance …

The emergence of anti-social behaviour in online environments presents a serious issue in
today's society. Automatic detection and identification of such behaviour are becoming …

Today online networking has become an indispensable part of life for people all over the
world. It is difficult for users to reduce their internet/online communications, as the flow of …

During the last decades, in the area of machine learning and data mining, the development
of ensemble methods has gained a significant attention from the scientific community …

Conventional personal identification methods (ID, password, authorization certificate, etc.)
entail various issues, including forgery or loss. Technological advances and the diffusion …

Text has traditionally been used to train automated classifiers for a multitude of purposes,
such as: classification, topic modelling and sentiment analysis. State-of-the-art LSTM …