Is there a Mean Average Recall for Item Retrieval/ Recommendation Systems?

Mean Average Precision for Information retrieval is computed using Average Precision @ k (AP@k). AP@k is measured by first computing Precision @ k (P@k) and then averaging the P@k only for the k's where the document in position k is relevant. I still don't understand why the remaining P@k's are not used, but that is not my question.

My question is: is there an equivalent Mean Average Recall (MAR) and Average Recall @ k (AR@k)? Recall @ k (R@k) is simple to compute.

References:

Topic model-evaluations evaluation information-retrieval recommender-system

Category Data Science

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