Design Strategies for Minimal Perfect Hash Functions.

A minimal perfect hash function h for a set S ⊆ U of size n is a function $h\colon U\to \{0,\ldots,n-1\}$ that is one-to-one on S. The complexity measures of interest are storage space for h, evaluation time (which should be constant), and construction time. The talk gives an overview of several recent randomized constructions of minimal perfect hash functions, leading to space-efficient solutions that are fast in practice. A central issue is a method ("split-and-share") that makes it possible to assume that fully random (hash) functions are available. [ABSTRACT FROM AUTHOR]