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Hash Adaptive Bloom Filter
[article]
2021
arXiv
pre-print
Bloom filter is a compact memory-efficient probabilistic data structure supporting membership testing, i.e., to check whether an element is in a given set. However, as Bloom filter maps each element with uniformly random hash functions, few flexibilities are provided even if the information of negative keys (elements are not in the set) are available. The problem gets worse when the misidentification of negative keys brings different costs. To address the above problems, we propose a new Hash
arXiv:2106.07037v1
fatcat:ewh3beb7j5afvb7ktdr444lk3q