Publication: CEDAR offers metadata recommendations from mined rules

Marcos Martinez-Romero and his co-authors have published a new paper describing CEDAR’s updated implementation of intelligent authoring. The new methods use rule mining to generate recommendations based on previously entered metadata in the CEDAR system, and offer the users only the most likely recommendations given previous metadata entries for the template.

Suggested values seen by users — The intelligent authoring metadata recommendations take into account rules derived from previously entered metadata with the same values.

You can find instructions for setting up this capability in the CEDAR User Manual page Understanding the Suggestion System.

Martínez-Romero M, O’Connor MJ, Egyedi AL, Willrett D, Hardi J, Graybeal J, Musen MA. Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases. Database. Volume 2019, 10 June 2019. https://doi.org/10.1093/database/baz059.