The article presents a workflow to create a question-answering system whose knowledge
base combines knowledge graphs and scientific publications on coronaviruses. It is based …

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become
powerful tools for the analysis of large collections of documents (such as papers, projects, or …

In the absence of sufficient medication for COVID patients due to the increased demand,
disused drugs have been employed or the doses of those available were modified by …

There are many scenarios where we may want to find pairs of textually similar documents in
a large corpus (eg a researcher doing literature review, or an R&D project manager …

Searching for similar documents and exploring major themes covered across groups of
documents are common activities when browsing collections of scientific papers. This …

Abstract The Easy-to-Read (E2R) Methodology was created to improve the daily life of
people with cognitive disabilities. This methodology aims to present clear and easily …

In probabilistic topic models, a topic is characterised by a set of words, with a probability
associated to each of them. Even though it is not necessary to understand the meaning of …

With the ongoing growth in number of digital articles in a wider set of languages and the
expanding use of different languages, we need annotation methods that enable browsing …

Summaries and abstracts of research papers have been tra-ditionally used for many
purposes by scientists, research practitioners, editors, programme committee members or …

Information retrieval has traditionally been approached using vector models to describe
texts. In large document collections, these models need to reduce the dimensions of the …