[Background.] Empirical research in requirements engineering (RE) is a constantly evolving
topic, with a growing number of publications. Several papers address this topic using …

The automatic semantic structuring of scientific text allows for more efficient reading of
research articles and is an important indexing step for academic search engines. Sequential …

In recent years, we saw the emergence of several approaches for producing machine-
readable, semantically rich, interlinked description of the content of research publications …

In recent decades, there has been a major shift towards improved digital access to scholarly
works. However, even now that these works are available in digital form, they remain …

Abstract In Natural Language Processing (NLP) domain, the majority of automatic text
summarization approaches depend on a prior knowledge of the language and/or the …

Sequential sentence classification deals with the categorisation of sentences based on their
content and context. Applied to scientific texts, it enables the automatic structuring of …

Purpose This paper aims to curate open research knowledge graph (ORKG) with papers
related to ontology learning and define an approach using ORKG as a computer-assisted …

Scholarly knowledge graphs provide researchers with a novel modality of information
retrieval, and their wider use in academia is beneficial for the digitalization of published …

Recent regulatory initiatives like the European AI Act and relevant voices in the Machine
Learning (ML) community stress the need to describe datasets along several key …

Purpose This study aims to evaluate a method of building a biomedical knowledge graph
(KG). Design/methodology/approach This research first constructs a COVID-19 KG on the …