Sistemas de recuperación de información implementados a partir de CORD-19: herramientas clave en la gestión de la información sobre COVID-19

Research on the coronavirus has generated an extraordinary production of scientific documents. Their treatment and assimilation by the scientific community has required the help of specifically designed information retrieval systems. Some of the world’s leading institutions involved in the fight against the pandemic have developed the CORD-19 dataset that stands out from other projects of a similar nature. The documents collected in this source have been processed by various information retrieval tools, sometimes prototypes or previously implemented systems. The typology and main characteristics of these systems have been analysed, concluding that there are three main non-exclusive categories among them: terminological search, information visualisation and natural language processing. It should be noted that most of them use semantic search technologies in order to facilitate the acquisition of knowledge by researchers and to help them in their enormous task. The crisis caused by the pandemic has been taken advantage of by semantic search engines to find their site

Instruments and Tools to Identify Radical Textual Content

The Internet and social networks are increasingly becoming a media of extremist propaganda. On homepages, in forums or chats, extremists spread their ideologies and world views, which are often contrary to the basic liberal democratic values of the European Union. It is not uncommon that violence is used against those of different faiths, those who think differently, and members of social minorities. This paper presents a set of instruments and tools developed to help investigators to better address hybrid security threats, i.e., threats that combine physical and cyber attacks. These tools have been designed and developed to support security authorities in identifying extremist propaganda on the Internet and classifying it in terms of its degree of danger. This concerns both extremist content on freely accessible Internet pages and content in closed chats. We illustrate the functionalities of the tools through an example related to radicalisation detection; the data used here are just a few tweets, emails propaganda, and darknet posts. This work was supported by the EU granted PREVISION (Prediction and Visual Intelligence for Security Intelligence) project

Getting Insights from a Large Corpus of Scientific Papers on Specialisted Comprehensive Topics - the Case of COVID-19

International audienceCOVID-19 is one of the most important topics these days, specifically on search engines and news. While fake news is easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific publications on COVID-19 and related research on PubMed, automatic computer-assisted analysis is required. In this paper, we develop two methodologies to get insights on specific sub-topics of interest and latest research sub-topics. These rely on natural language processing and graph-based visualizations. We run these methodologies on two cases: the virus origin and the uses of existing drugs