• An automatic information extraction syst

    From ScienceDaily@1:317/3 to All on Wednesday, March 30, 2022 22:30:44
    An automatic information extraction system for scientific articles on
    COVID-19

    Date:
    March 30, 2022
    Source:
    University of the Basque Country
    Summary:
    VIGICOVID is a system that uses natural language questions to get
    answers in the avalanche of information on COVID-19 and SARS-CoV-2.



    FULL STORY ==========================================================================
    The global bio-health research community is making a tremendous effort to generate knowledge relating to COVID-19 and SARS-CoV-2. In practice, this effort means a huge, very rapid production of scientific publications,
    which makes it difficult to consult and analyse all the information. That
    is why experts and decision-making bodies need to be provided with
    information systems to enable them to acquire the knowledge they need.


    ==========================================================================
    This is precisely what has been explored in the VIGICOVID researchers
    project run by the UPV/EHU's HiTZ Centre, the UNED's NLP & IR group,
    and Elhuyar's Artificial Intelligence and Language Technologies Unit,
    thanks to Fondo Supera COVID-19 funding awarded by the CRUE. In the study, under the coordination of the UNED research group they have created
    a prototype to extract information through questions and answers in
    natural language from an updated set of scientific articles on COVID-19
    and SARS-CoV-2 published by the global research community.

    "The information search paradigm is changing thanks to artificial intelligence," said Eneko Agirre, head of the UPV/EHU's HiTZ
    Centre. "Until now, when searching for information on the internet,
    a question is entered, and the answer has to be sought in the documents displayed by the system. However, in line with the new paradigm, systems
    that provide the answer directly without any need to read the whole
    document are becoming more and more widespread." In this system,
    "the user does not request information using keywords, but asks a
    question directly," explained Elhuyar researcher Xabier Saralegi. The
    system searches for answers to this question in two steps: "Firstly,
    it retrieves documents that may contain the answer to the question asked
    by using a technology that combines keywords with direct questions. That
    is why we have explored neural architectures," added Dr Saralegi. Deep
    neural architectures fed with examples were used: "That means that
    search models and question answering models are trained by means of deep machine learning." Once the set of documents has been extracted, they
    are reprocessed through a question and answer system in order to obtain specific answers: "We have built the engine that answers the questions;
    when the engine is given a question and a document, it is able to detect whether or not the answer is in the document, and if it is, it tells us
    exactly where it is," explained Dr Agirre.

    A readily marketable prototype The researchers are satisfied with the
    results of their research: "From the techniques and evaluations we
    analysed in our experiments, we took those that give the prototype the
    best results," said the Elhuyar researcher. A solid technological base
    has been established, and several scientific papers on the subject have
    been published. "We have come up with another way of running searches
    for whenever information is urgently needed, and this facilitates the information use process. On the research level, we have shown that the
    proposed technology works, and that the system provides good results,"
    Agirre pointed out.

    "Our result is a prototype of a basic research project. It is not a
    commercial product," stressed Saralegi. But such prototypes can be
    modelled easily within a short time, which means they can be marketed
    and made available to society.

    These researchers stress that artificial intelligence enables increasingly powerful tools to be made available for working with large document
    bases. "We are making very rapid progress in this area. And what is
    more, everything that is investigated can readily reach the market,"
    concluded the UPV/EHU researcher.


    ========================================================================== Story Source: Materials provided by
    University_of_the_Basque_Country. Note: Content may be edited for style
    and length.


    ========================================================================== Journal Reference:
    1. Arantxa Otegi, In~aki San Vicente, Xabier Saralegi, Anselmo
    Pen~as, Borja
    Lozano, Eneko Agirre. Information retrieval and question answering:
    A case study on COVID-19 scientific literature. Knowledge-Based
    Systems, 2022; 240: 108072 DOI: 10.1016/j.knosys.2021.108072 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/03/220330103258.htm

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