How the Obscure Features Hypothesis Leads to Innovation Assistant Software

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Reference

Tony McCaffrey and Lee Spector: How the Obscure Features Hypothesis Leads to Innovation Assistant Software. In: Computational Creativity 2011 ICCC 2011, pp. 120-122.

DOI

Abstract

A new cognitive theory of innovation, the Obscure Features Hypothesis (OFH), states that almost all inno- vative solutions result from two steps: (1) noticing a rarely noticed or never-before noticed (i.e., obscure) feature of the problem’s elements, and (2) building a solution based on that obscure feature (McCaffrey 2011). Structural properties of the human semantic network make it possible to locate useful obscure fea- tures with a high probability. Innovation Assistant (IA) software interactively guides human users to the most likely obscure features for solving the problem at hand.

Extended Abstract

Bibtex

@inproceedings{
author = {Tony McCaffrey and Lee Spector},
title = {How the Obscure Features Hypothesis Leads to Innovation Assistant Software},
editor = {Dan Ventura, Pablo Gervás, D. Fox Harrell, Mary Lou Maher, Alison Pease and Geraint Wiggins},
booktitle = {Proceedings of the Second International Conference on Computational Creativity},
series = {ICCC2011},
year = {2011},
month = {April},
location = {México City, México},
pages = {120-122},
url = {http://iccc11.cua.uam.mx/proceedings/the_helpful/mccaffrey_iccc11.pdf, http://de.evo-art.org/index.php?title=How_the_Obscure_Features_Hypothesis_Leads_to_Innovation_Assistant_Software },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}

Used References

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McCaffrey, A. J. (2011). The obscure features hypothesis for innovation: One key to improving human innovation. Unpublished doctoral dissertation, University of Massa- chusetts Amherst.

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Links

Full Text

http://iccc11.cua.uam.mx/proceedings/the_helpful/mccaffrey_iccc11.pdf

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