%-------------------------------------------------------------------------------
% UF Sparse Matrix Collection, Tim Davis
% http://www.cise.ufl.edu/research/sparse/matrices/Pajek/Wordnet3
% name: Pajek/Wordnet3
% [Pajek network: Wordnet3 dictionary network]
% id: 1531
% date: 2006
% author: 
% ed: V. Batagelj
% fields: name title A id kind notes aux date author ed
% aux: edgecode nodecode category nodename
% kind: directed weighted graph
%-------------------------------------------------------------------------------
% 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.                                            
% ------------------------------------------------------------------------------
%-------------------------------------------------------------------------------
