Hunch Mining: Intuition Augmented with Cognitive Computing, Analytics, and Artificial Intelligence

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dc.contributor.authorNelson, Jim
dc.contributor.authorClark, Terry
dc.contributor.authorStewart, Ian
dc.date.accessioned2017-12-28T02:12:17Z
dc.date.available2017-12-28T02:12:17Z
dc.date.issued2018-01-03
dc.description.abstractHunches are important tools for executives making time-critical highly complex decisions in turbulent environments. However, hunches are also elusive and exist below the surface when not being used for immediate decision making. These latent hunches can be useful for developing analytical models. This paper coins the term "hunch mining" to describe the process of surfacing latent hunches from corporate decision makers as well as workers and using them as models for data analytics. We present the Organizational Hunch Matrix and show how organizations can make the leap from time-consuming manual cognitive analysis to artificial intelligence and analytics driven analysis facilitated by Cognitive Computing Engineers.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2018.633
dc.identifier.isbn978-0-9981331-1-9
dc.identifier.urihttp://hdl.handle.net/10125/50522
dc.language.isoeng
dc.relation.ispartofProceedings of the 51st Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPractice-based IS Research
dc.subjectAnalytics, Artificial Intelligence, Cognitive Computing, Executive Decisions, Text Mining
dc.titleHunch Mining: Intuition Augmented with Cognitive Computing, Analytics, and Artificial Intelligence
dc.typeConference Paper
dc.type.dcmiText

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