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Knowledge Enhanced Discovery Systems

Incorporating Background Knowledge for Scientific Discovery


Principal Investigators:
Marie desJardins (UMBC)
Kiri Wagstaff (JPL)

The overall goal of this project is to develop and evaluate methods for incorporating existing knowledge into scientific discovery methods. We have divided this goal into three main areas:

  • Trainable classification methods
  • Exploratory clustering methods
  • Modeling and learning user preferences for automatic ranking of items.

KEDS is funded by the United States National Science Foundation, NSF award number 0325329. For more information about NSF, visit www.nsf.gov