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A Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set.
The Bloom filter, dating back to 1970 [1], is the data structure underlying “supertrace” [12], “multihash- ing” [21], and “bitstate hashing” [13].
In this paper, we show how to obtain Bloom filters that are simultaneously fast, accurate, memory-efficient, scalable, and flexible.
Bloom filters have been criticized for being slow, inaccurate, and memory-inefficient, but in this paper, we show how to obtain Bloom filters that are ...
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These graphs show the accuracy of three probabilistic verification techniques/ configurations for various state space sizes. In both graphs, lower is better.
Bloom filters have been criticised for being slow, inaccurate, and memory-inefficient, but in this paper, we show how to obtain Bloom filters that are ...
Feb 10, 2018 · A Bloom filter guarantees certainty when it tells you an element is not in a set, but can only give you a probability of whether the element was ...
Jun 28, 2024 · Bloom filters, invented by Burton Howard Bloom in 1970, are space-efficient probabilistic data structures designed to test whether an element is a member of a ...
Jun 26, 2023 · A Bloom filter is a special kind of data structure that allows us to quickly check if an item is a member of a set.
A Bloom filter is a probabilistic data structure which provides an efficient way to verify that an entry is certainly not in a set.
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