Documents are stored in a digital form across several organizations. Printing this amount of
data and placing it into folders instead of storing digitally is against the practical, economical …

We extend our previous work on Inductive Conformal Prediction (ICP) for multi-label text
classification and present a novel approach for addressing the computational inefficiency of …

Recently the deep learning techniques have achieved success in multi-label classification
due to its automatic representation learning ability and the end-to-end learning framework …

Big data technology has gained attention in all fields, particularly with regard to research
and financial institutions. This technology has changed the world tremendously …

Due to the mass availability of textual data on Web, text classification (TC), classifying texts
into predetermined sets becomes a spotlight for researchers. A number of TC applications …

Non-invasive acoustic analyses of voice disorders have been at the forefront of current
biomedical research. Usual strategies, essentially based on machine learning (ML) …

In this paper, we present our progress in pre-training monolingual Transformers for Czech
and contribute to the research community by releasing our models for public. The need for …

This paper describes our system created to detect stance in online discussions. The goal is
to identify whether the author of a comment is in favor of the given target or against. We …

Malware domains generated by Domain Generated Algorithms (DGA) are highly dynamic in
nature. The traditional approach of blacklisting the malicious domains is a time consuming …

This paper deals with the automatic classification of medical reports in the form of
unstructured texts in Czech. The outcomes of this work are intended to be integrated into a …