The Future role of Big Data and machine learning in health and safety inspection efficiency
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Tag | 1 | 2 | Value |
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LDR | 00000cam a22000004b 4500 | ||
001 | MAP20190020091 | ||
003 | MAP | ||
005 | 20220911211401.0 | ||
008 | 140709s2019 lux|||| ||| ||eng d | ||
040 | $aMAP$bspa$dMAP | ||
084 | $a870 | ||
100 | 1 | $0MAPA20190008792$aDahl, Øyvind | |
245 | 1 | 4 | $aThe Future role of Big Data and machine learning in health and safety inspection efficiency$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 | |
700 | 1 | $0MAPA20190008808$aStarren, Annick | |
710 | 2 | $0MAPA20080466893$aEuropean Agency for Safety and Health at Work |