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  • Big Data  (1)
  • J21  (1)
  • 1
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    Brasília: Instituto de Pesquisa Econômica Aplicada (IPEA)
    Publication Date: 2020-01-17
    Description: 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
    Keywords: C52 ; C55 ; C65 ; C80 ; C88 ; ddc:330 ; pairs linking ; blocking ; administrative records ; Big Data ; R
    Language: Portuguese
    Type: doc-type:workingPaper
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  • 2
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    Brasília: Instituto de Pesquisa Econômica Aplicada (IPEA)
    Publication Date: 2020-01-17
    Description: 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.
    Keywords: J24 ; J64 ; Q55 ; N36 ; J21 ; ddc:330 ; automation ; labor market ; artificial intelligence ; natural language processing ; technical expertise ; text mining
    Language: Portuguese
    Type: doc-type:workingPaper
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