5. The method of claim 4 , further comprising learning weights for the parameterized ranking function based on user feedback data.
4. The method of claim 1 , further comprising: determining one or more term scores for at least each particular metadata item in the candidate set of metadata items, the one or more term scores being based on at least one of the frequency with which the term appears in the particular metadata item or the frequency with which the term appears in all of the metadata items; for each particular metadata item in the candidate set of the metadata items, determining an instance frequency score based at least in part on how many data objects in the data repository are instances of the particular metadata item; wherein calculating the ranking score for each particular metadata item comprises inputting at least the relationship score for the particular metadata item, the one or more term scores for the particular metadata item, and the instance frequency score into a parameterized ranking function.