Matrix properties
number of rows	82,670
number of columns	82,670
nonzeros	132,964
# strongly connected comp.	67,689
explicit zero entries	0
nonzero pattern symmetry	18%
numeric value symmetry	17%
type	integer
structure	unsymmetric
Cholesky candidate?	no
positive definite?	no

author
editor	V. Batagelj
date	2006
kind	directed weighted graph
2D/3D problem?	no

Additional fields	size and type
edgecode	full 9-by-28
nodecode	full 5-by-4
category	full 82670-by-1
nodename	full 82670-by-69

Notes:

------------------------------------------------------------------------------
Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,
http://vlado.fmf.uni-lj.si/pub/networks/data/.                                
------------------------------------------------------------------------------
NOTE: this is a binary graph in the Pajek dataset, but where each edge has a  
label (not a weight) in the range 1 to 9.  The following labels are used:     
1  hypernym pointer                                                           
2  entailment pointer                                                         
3  similar pointer                                                            
4  member meronym pointer                                                     
5  substance meronym pointer                                                  
6  part meronym pointer                                                       
7  cause pointer                                                              
8  grouped pointer                                                            
9  attribute pointer                                                          
This is not a multigraph.  There are no edges (i,j) between the same nodes    
with the same label.  Thus, in the sparse matrix, the edge weight A(i,j)      
represents the label 1 through 9 of edge (i,j).  No loss of information       
occurs in this translation.  The above table is in aux.edgecode(1:9,:).       
Each node is a word in a dictionary.  aux.category(i) gives the category      
of the word:                                                                  
   1: n (noun?)       63099 words                                             
   3: a (adjective?)   5501 words                                             
   4: r (?)            2846 words                                             
   5: s (?)            6728 words.                                            
------------------------------------------------------------------------------

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.