How DoD's TRA process could be applied to intelligent systems development

Sparrow, D.A.; Cazares, Shelley M

doi:10.1145/1660877.1660881

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2012

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“…We are considering the cardinality of author sets only, but not all vertices are created equally-some authors are more influential than others and should carry more weight in our privy analysis. Similarly, not all edges are created equally-some papers are more important than others, and perhaps a maturity index such as the Technology Readiness Level [32] could be usefully employed. We have considered priviness as a binary property.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Horizon Scanning for Mitigating Technological Surprise: Detecting the Potential for Collaboration at the Interface

Priebe

Solka

Marchette

et al. 2012

Statistical Analysis

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'The identification of potential breakthroughs before they happen' is a vague data analysis problem and 'the scientific literature' is a massive, complex dataset. Hence QHS for MTS might seem to be prototypical of the data miner's lament: 'Here's some data we have. . . can you find something interesting?' Nonetheless, the problem is real and important, and we develop an innovative statistical approach thereto-not a final etched-in-stone approach, but perhaps the first complete quantitative methodology explicitly addressing QHS for MTS.

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Section: Discussionmentioning

confidence: 99%