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  • 1
    Online Resource
    Online Resource
    Rio de Janeiro : Instituto de Pesquisa Econômica Aplicada
    Pages: 1 Online-Ressource (circa 56 Seiten) , Illustrationen
    Series Statement: Texto para discussão / Ipea 2420
    Description / Table of Contents: This paper verified the predictive performance of probabilistic record linkage algorithms for the integration big sized real databases, evaluating the effects of the blocking key definition, as well as string metric functions and phonetic code pairing algorithms with respect to the prediction's quality and computational complexity. A bibliographical survey of the main deterministic and probabilistic record linkage methods was carried out, as well as of recent advances combining machine learning techniques and main packages and implementations available in open-source R language. The results can provide heuristics for problems of administrative records integration at national level and have potential value for the formulation and evaluation of public policies
    Note: Zusammenfassung in portugiesischer Sprache
    Language: Portuguese
    URL: Volltext  (Kostenfrei)
    URL: Volltext  (Kostenfrei)
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  • 2
    Online Resource
    Online Resource
    Common title
    ISSN: 1466-4313
    In: Applied mathematical finance, London : Routledge, 1994, 26(2019), 1, Seite 69-100, 1466-4313
    Language: English
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  • 3
    Online Resource
    Online Resource
    Common title
    ISSN: 1528-6932
    In: Latin American business review, Binghamton, NY : Routledge, Taylor & Francis Group, 1998, 20(2019), 3, Seite 227-248, 1528-6932
    Language: English
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  • 4
    Online Resource
    Online Resource
    Brasília : Instituto de Pesquisa Econômica Aplicada
    Pages: 1 Online-Ressource (circa 40 Seiten) , Illustrationen
    Series Statement: Texto para discussão / Ipea 2457
    Description / Table of Contents: This work aimed to reproduce the methodology of Carl Benedikt Frey and Michael Osborne of 2017 for estimating the automation probabilities of occupations in Brazil. These estimates are potentially important for professionals and policymakers because they can guide the career of a worker, as well as define priority courses that educational institutions should offer in order to maximize employment opportunities in the country. We consulted the opinion of 69 scholars and professionals that are experts in machine learning to ground the estimation the automation probability of Brazilian occupations. The findings indicate that a large part of the occupations can be automated in the next years. In addition, it can be seen that these professions with a higher risk of automation show a trend of growth over time, which may result in a high level of unemployment in the coming years if professionals and the government do not prepare for this scenario.
    Note: Zusammenfassung in portugiesischer Sprache
    Language: Portuguese
    URL: Volltext  (Kostenfrei)
    URL: Volltext  (Kostenfrei)
    Location Call Number Limitation Availability
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