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  4. Advances in Risk Analysis with Big Data
 
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Advances in Risk Analysis with Big Data

Journal
Risk Analysis
Journal Volume
37
Journal Issue
8
Pages
1435-1442
Date Issued
2017
Author(s)
TSAN MING CHOI  
Lambert J.H.
DOI
10.1111/risa.12859
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027398105&doi=10.1111%2frisa.12859&partnerID=40&md5=e95e983ae21d7f991f9fee1fc9d24596
https://scholars.lib.ntu.edu.tw/handle/123456789/612252
Abstract
With cloud computing, Internet-of-things, wireless sensors, social media, fast storage and retrieval, etc., organizations and enterprises have access to unprecedented amounts and varieties of data. Current risk analysis methodology and applications are experiencing related advances and breakthroughs. For example, highway operations data are readily available, and making use of them reduces risks of traffic crashes and travel delays. Massive data of financial and enterprise systems support decision making under risk by individuals, industries, regulators, etc. In this introductory article, we first discuss the meaning of big data for risk analysis. We then examine recent advances in risk analysis with big data in several topic areas. For each area, we identify and introduce the relevant articles that are featured in the special issue. We conclude with a discussion on future research opportunities. ? 2017 Society for Risk Analysis
Subjects
Big data; data analytics; risk analysis; risk assessment; risk communication; risk management; security
Other Subjects
adult; article; big data; decision making; human; risk assessment; risk management
Publisher
Blackwell Publishing Inc.
Type
editorial

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