TY - GEN
T1 - Classifying scientific performance on a metric-by-metric basis
AU - Bell, Eric
AU - Marshall, Eric
AU - Hull, Ryan
AU - Fligg, Keith
AU - Sanfilippo, Antonio
AU - Daly, Don
AU - Engel, Dave
PY - 2012
Y1 - 2012
N2 - In this paper, we outline a system for evaluating the performance of scientific research across a number of outcome metrics (e.g. publications, sales, new hires). Our system is designed to classify research performance into a number of metrics, evaluate each metric's performance using only data on other metrics, and to cast predictions of future performance by metric. This study shows how data mining techniques can be used to provide a predictive analytic approach to the management of resources for scientific research.
AB - In this paper, we outline a system for evaluating the performance of scientific research across a number of outcome metrics (e.g. publications, sales, new hires). Our system is designed to classify research performance into a number of metrics, evaluate each metric's performance using only data on other metrics, and to cast predictions of future performance by metric. This study shows how data mining techniques can be used to provide a predictive analytic approach to the management of resources for scientific research.
UR - https://www.scopus.com/pages/publications/84865008767
M3 - Conference contribution
AN - SCOPUS:84865008767
SN - 9781577355588
T3 - Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25
SP - 400
EP - 403
BT - Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25
T2 - 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25
Y2 - 23 May 2012 through 25 May 2012
ER -