Random indexing revisited

Abstract

Random indexing is a method for constructing vector spaces at a reduced dimensionality. Previously, the method has been proposed using Kanerva’s sparse distributed memory model. Although intuitively plausible, this description fails to provide mathematical justification for setting the method’s parameters. The random indexing method is revisited using the principles of sparse random projections in Euclidean spaces in order to complement its previous delineation.