Towards real-time probabilistic risk assessment by sensing disruptive events from streamed news feeds

Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X, Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646, Pauran, Nargis and Bowen, Philip John ORCID: https://orcid.org/0000-0002-3644-6878 2014. Towards real-time probabilistic risk assessment by sensing disruptive events from streamed news feeds. Presented at: 8th IEEE International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2014), Birmingham City University, Birmingham, UK., 2-4 July 2014. -.

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Abstract

Risk management has become an important con- cern over recent years and understanding how risk models could be developed based on the availability of real time (streaming) data has become a challenge. As the volume and velocity of event data (from news media, for instance) continues to grow, we investigate how such data can be used to inform the development of dynamic risk models. A Bayesian Belief Network based approach is adopted in this work, which is able to make use of priors derived from a variety of different news sources (based on data available in RSS feeds).

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Completion
Status:	Unpublished
Schools:	Engineering Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date of First Compliant Deposit:	30 March 2016
Last Modified:	27 Oct 2022 09:11
URI:	https://orca.cardiff.ac.uk/id/eprint/64708

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