I was wondering if there's a good way to use ensembling when I have two or more algoritims producing ranked lists. That is, suppose I have the following datasets consisting of ordered lists (higher to the top means more relevant):

Method1_Rankings  Method2_Rankings GoldStandard_Rankings
item1             item2             item1
item3             item1             item3
item2             item10            item5

Is there a way to optimally combine methods 1 and 2 (e.g., give the rankings some weights or similar)? Thank you.


1 Answer 1


In this case, you might want to convert these into pair-wise relationships (e.g. item1 < item3), put together what you get from the different methods, and find a ranking which agrees with them the most.

You can look at the answer in the comment for some ideas - I would also suggest another paper that might help you: Aggregating inconsistent information: ranking and clustering


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.