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Definition
The Reciprocal Rank (RR) information retrieval measure calculates the reciprocal of the rank at which the first relevant document was retrieved. RR is 1 if a relevant document was retrieved at rank 1, if not it is 0.5 if a relevant document was retrieved at rank 2 and so on. When averaged across queries, the measure is called the Mean Reciprocal Rank (MRR).
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Mean Reciprocal Rank is associated with a user model where the user only wishes to see one relevant document. Assuming that the user will look down the ranking until a relevant document is found, and that document is at rank n, then the precision of the set they view is 1/n, which is also the reciprocal rank measure. For this reason, MRR is equivalent to Mean Average Precision in cases where each query has precisely one relevant document. MRR is not a shallow measure, in that its value changes whenever the required document is moved, although the change is much larger when moving from rank 1 to rank 2 (change is 0.5) compared to moving from rank 100 to 1,000 (change of 0.009).
MRR is an appropriate measure for known item search, where the user is trying to find a document that he either has seen before or knows to exist. This is called navigational search in the case of web search. In a case where there are multiple copies of the required document, or otherwise a set of relevant documents that are substitutes, MRR can still be applied based on the first copy.
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© 2009 Springer Science+Business Media, LLC
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Craswell, N. (2009). Mean Reciprocal Rank. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_488
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DOI: https://doi.org/10.1007/978-0-387-39940-9_488
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-35544-3
Online ISBN: 978-0-387-39940-9
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