Semi-supervised learning (SSL) has tremendous value in practice due to the utilization of
both labeled and unlabelled data. An essential class of SSL methods, referred to as graph …

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …

This book presents the features and advantages offered by complex networks in the
machine learning domain. In the first part, an overview on complex networks and network …

Fake news can rapidly spread through internet users and can deceive a large audience.
Due to those characteristics, they can have a direct impact on political and economic events …

Abstract Aspect-Based Sentiment Analysis (ABSA) is a promising approach to analyze
consumer reviews at a high level of detail, where the opinion about each feature of the …

The word sense disambiguation (WSD) task aims at identifying the meaning of words in a
given context for specific words conveying multiple meanings. This task plays a prominent …

High dimensional data classification with very limited labeled training data is a challenging
task in the area of data mining. In order to tackle this task, we first propose a feature …

Transductive classification is a useful way to classify texts when labeled training examples
are insufficient. Several algorithms to perform transductive classification considering text …

Semisupervised learning methods are often adopted to handle datasets with very small
number of labeled samples. However, conventional semisupervised ensemble learning …

Classification of high-dimensional data with very limited labels is a challenging task in the
field of data mining and machine learning. In this paper, we propose the multiobjective …