Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50522

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

File Size Format  
paper0635.pdf 826.78 kB Adobe PDF View/Open

Item Summary

dc.contributor.author Nelson, Jim
dc.contributor.author Clark, Terry
dc.contributor.author Stewart, Ian
dc.date.accessioned 2017-12-28T02:12:17Z
dc.date.available 2017-12-28T02:12:17Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50522
dc.description.abstract Hunches 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.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Practice-based IS Research
dc.subject Analytics, Artificial Intelligence, Cognitive Computing, Executive Decisions, Text Mining
dc.title Hunch Mining: Intuition Augmented with Cognitive Computing, Analytics, and Artificial Intelligence
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.633
Appears in Collections: Practice-based IS Research


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons