Distance-Sensitive Bloom Filters
Adam Kirsch, Michael Mitzenmacher · 2006
A Bloom filter is a space-efficient data structure that answers set membership queries with some chance of a false positive. We introduce the problem of designing generalizations of Bloom filters designed to answer queries of the form, “Is x close to an element of S?” where closeness is measured under a suitable metric. Such a data structure would have several natural applications in networking and database applications. We demonstrate how appropriate data structures can be designed using locality-sensitive hash functions as a building block, and we specifically analyze the performance of a natural scheme under the Hamming metric.