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A Lower Bound for Dynamic Approximate Membership Data Structures
2010 IEEE 51st Annual Symposium on Foundations of Computer Science
An approximate membership data structure is a randomized data structure for representing a set which supports membership queries. It allows for a small false positive error rate but has no false negative errors. Such data structures were first introduced by Bloom in the 1970's, and have since had numerous applications, mainly in distributed systems, database systems, and networks. The algorithm of Bloom is quite effective: it can store a set S of size n by using only ≈ 1.44n log 2 (1/ ) bitsdoi:10.1109/focs.2010.81 dblp:conf/focs/LovettP10 fatcat:zb6eirekujgjjcz3yu22oyum4a