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The Future role of Big Data and machine learning in health and safety inspection efficiency

Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
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001  MAP20190020091
003  MAP
005  20220911211401.0
008  140709s2019 lux|||| ||| ||eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎870
1001 ‎$0‎MAPA20190008792‎$a‎Dahl, Øyvind
24514‎$a‎The Future role of Big Data and machine learning in health and safety inspection efficiency‎$c‎Øyvind Dahl, Annick Starren
260  ‎$a‎Luxembourg‎$b‎Publications Office of the European Union‎$c‎2019
300  ‎$a‎7 p.
500  ‎$a‎Resumen ejecutivo en español
520  ‎$a‎Most labour inspectorates collect and store huge amounts of data related to their inspection objects and their inspection activities. Thus, inspectorates potentially possess large and rapidly growing volumes of data, nowadays referred to by the term big data'. Big data, combined with machine learning technology, is being used at an increasing rate for different predictive purposes, by learning from hidden trends in the data. For example, the predictive value of big data and machine learning techniques are being tested in areas as diverse as cancer prognosis and patient outcomes, bankruptcy prediction, oil price prediction, tax fraud detection, crime prediction and stock market forecasting. The fundamental question being addressed in this paper, however, is whether or not the use of big data and machine learning technology to target high-risk inspection objects is a promising avenue for labour inspectorates.
650 1‎$0‎MAPA20080629724‎$a‎Seguridad e higiene en el trabajo
650 4‎$0‎MAPA20080627416‎$a‎Prevención de riesgos laborales
650 4‎$0‎MAPA20080604974‎$a‎Campañas de prevención
650 4‎$0‎MAPA20080602116‎$a‎Inspección de trabajo
650 4‎$0‎MAPA20140022717‎$a‎Big data
651 1‎$0‎MAPA20080637743‎$a‎Europa
7001 ‎$0‎MAPA20190008808‎$a‎Starren, Annick
7102 ‎$0‎MAPA20080466893‎$a‎European Agency for Safety and Health at Work