0000000000714492

AUTHOR

A. L. Buchsbaum

showing 2 related works from this author

Table Compression

2016

Data Compression Techniques for massive tables are described. Related methodological results are also presented.

Compression and transmission of tableSettore INF/01 - InformaticaBig Data ManagementStorageCompressive estimates of entropyData Compression. Algorithms. Data structuresCompression of multidimensional data
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New results for finding common neighborhoods in massive graphs in the data stream model

2008

AbstractWe consider the problem of finding pairs of vertices that share large common neighborhoods in massive graphs. We give lower bounds for randomized, two-sided error algorithms that solve this problem in the data-stream model of computation. Our results correct and improve those of Buchsbaum, Giancarlo, and Westbrook [On finding common neighborhoods in massive graphs, Theoretical Computer Science, 299 (1–3) 707–718 (2004)]

Data streamDiscrete mathematicsGeneral Computer ScienceExtremal graph theorySpace lower boundsModel of computationCommunication complexityGraph theoryUpper and lower boundsTheoretical Computer ScienceExtremal graph theoryCombinatoricsGraph algorithms for data streamsAlgorithms Theoretical Computer SciencedGraph algorithmsCommunication complexityComputer Science(all)MathematicsTheoretical Computer Science
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