Progressive Random Indexing: Dimensionality Reduction Preserving Local Network Dependencies

Abstract

The vector space model is undoubtedly among the most popular data representation models used in the processing of large networks. Unfortunately, the vector space model suffers from the so-called curse of dimensionality, a phenomenon where data become extremely sparse due to an exponential growth of the data space volume caused by a large number of… (More)
DOI: 10.1145/2996185

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