Matrix: Pajek/EAT_SR

Description: Pajek network: Edinburgh Associative Thesaurus (stimulus-response)

Pajek/EAT_SR graph Pajek/EAT_SR graph
(bipartite graph drawing) (graph drawing of A+A')

scc of Pajek/EAT_SR

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  • Matrix group: Pajek
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  • download as a MATLAB mat-file, file size: 1006 KB. Use UFget(1462) or UFget('Pajek/EAT_SR') in MATLAB.
  • download in Matrix Market format, file size: 1 MB.
  • download in Rutherford/Boeing format, file size: 1 MB.

    Matrix properties
    number of rows23,219
    number of columns23,219
    # strongly connected comp.15,466
    explicit zero entries0
    nonzero pattern symmetry 12%
    numeric value symmetry 3%
    Cholesky candidate?no
    positive definite?no

    authorG. Kiss, C. Armstrong R. Milroy, J. Piper
    editorV. Batagelj
    kinddirected weighted graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 23219-by-20


    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,                                
     EAT - The Edinburgh Associative Thesaurus /                                  
     The EAT is a database of word association norms.                             
     - Original EAT: George Kiss, Christine Armstrong,                            
     Robert Milroy and J.R.I. Piper (1968-1971).                                  
     - MRC Psycholinguistic Database Version modified by:                         
     Max Coltheart, S. James, J. Ramshaw, B.M. Philip,                            
     B. Reid, J. Benyon-Tinker and E. Doctor;                                     
     made available by: Philip Quinlan.                                           
     - The present version was re-structured and documented                       
     by Michael Wilson at the Rutherford Appleton Laboratory.                                                 
     transformed in Pajek format: V. Batagelj, 31. July 2003                      

    SVD-based statistics:
    null space dimension15,009
    full numerical rank?no
    singular value gap1.66891e+12

    singular values (MAT file):click here
    SVD method used:s = svd (full (A))

    Pajek/EAT_SR svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.