Bloom filters are a classic data structure used for set membership testing with probabilistic false positives. They have found applications in various fields, including distributed systems, networking, databases, and more. Below are some of the most important and influential papers on Bloom filters:
- Author: Burton H. Bloom (1970)
- Link: Original Paper
- Summary: This is the seminal paper where Burton H. Bloom introduced the concept of Bloom filters. It laid the foundation for using hash functions to test whether an element is in a set while allowing a small probability of false positives. This paper defines the key properties of the Bloom filter and establishes the basic trade-offs between space and time.
- Authors: R. M. Karp, M. Luby, and J. Feigenbaum (1995)
- Link: [Original