Unverified50% confidenceFactExact time
hit 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.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
Partially VerifiedThe Recall@k metric is defined as the proportion of the top k results that contain known relevant documents.71% similarUnverifiedThe core metrics for evaluating vector indexes include recall (Recall@k), P99 latency, QPS (throughput), index build time and memory.64% similarUnverifiedRecall@k is defined as: the number of expected text chunks that were retrieved divided by the total number of expected text chunks.59% similarUnverifiedThe feature in question divides the cumulative trading volume from market open to the current minute by the total trading volume for the day (the sum from open to close) as a normalization factor, causing intraday feature values to depend on information that is only available after the close.59% similarUnverifiedDuring peak hours, location data write volumes can reach millions of times per second, and such systems typically rely on time-series databases or message queues (such as Kafka) to handle high-concurrency writes.56% similar
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