Random indexing revisited
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Qasemizadeh, Behrang (2015). Random indexing revisited. Paper presented at the 20th International Conference on Applications of Natural Language to Information Systems, NLDB, Passau, Germany.
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.