Verified70% confidenceFactExact time
The Recall@k metric is defined as the proportion of the top k results that contain known relevant documents.
4
Sources
70%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedRecall@k is defined as: the number of expected text chunks that were retrieved divided by the total number of expected text chunks.79% similarUnverifiedhit rate usually refers to 'the proportion of queries that hit at least one relevant document', is a binary judgment and does not consider the rank of the hit; recall@k measures the proportion of all relevant documents recalled in the Top-K, and is a continuous value.71% similarUnverifiedThe core metrics for evaluating vector indexes include recall (Recall@k), P99 latency, QPS (throughput), index build time and memory.68% similarUnverifiedThe recency effect refers to information at the end of a sequence being more easily remembered.58% similar
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