%-------------------------------------------------------------------------------
% SuiteSparse Matrix Collection, Tim Davis
% https://sparse.tamu.edu/SNAP/com-DBLP
% name: SNAP/com-DBLP
% [SNAP network: DBLP collaboration network and ground-truth communities]
% id: 2779
% date: 2012
% author: J. Yang, J. Leskovec
% ed: J. Leskovec
% fields: name title A id date author ed kind notes aux
% aux: nodeid Communities_all Communities_top5000
% kind: undirected graph with communities
%-------------------------------------------------------------------------------
% notes:
% SNAP (Stanford Network Analysis Platform) Large Network Dataset Collection,
% Jure Leskovec and Anrej Krevl, http://snap.stanford.edu/data, June 2014.   
% email: jure at cs.stanford.edu                                             
%                                                                            
% DBLP collaboration network and ground-truth communities                    
%                                                                            
% https://snap.stanford.edu/data/com-DBLP.html                               
%                                                                            
% Dataset information                                                        
%                                                                            
% The DBLP (http://dblp.uni-trier.de/) computer science bibliography provides
% a comprehensive list of research papers in computer science. We construct a
% co-authorship network where two authors are connected if they publish at   
% least one paper together.  Publication venue, e.g, journal or conference,  
% defines an individual ground-truth community; authors who published to a   
% certain journal or conference form a community.                            
%                                                                            
% We regard each connected component in a group as a separate ground-truth   
% community. We remove the ground-truth communities which have less than 3   
% nodes.  We also provide the top 5,000 communities with highest quality     
% which are described in our paper (http://arxiv.org/abs/1205.6233). As for  
% the network, we provide the largest connected component.                   
%                                                                            
% Dataset statistics                                                         
% Nodes   317080                                                             
% Edges   1049866                                                            
% Nodes in largest WCC    317080 (1.000)                                     
% Edges in largest WCC    1049866 (1.000)                                    
% Nodes in largest SCC    317080 (1.000)                                     
% Edges in largest SCC    1049866 (1.000)                                    
% Average clustering coefficient  0.6324                                     
% Number of triangles 2224385                                                
% Fraction of closed triangles    0.1283                                     
% Diameter (longest shortest path)    21                                     
% 90-percentile effective diameter    8                                      
%                                                                            
% Source (citation)                                                          
% J. Yang and J. Leskovec. Defining and Evaluating Network Communities based 
% on Ground-truth. ICDM, 2012.  http://arxiv.org/abs/1205.6233               
%                                                                            
% Files                                                                      
% File    Description                                                        
% com-dblp.ungraph.txt.gz Undirected DBLP co-authorship network              
% com-dblp.all.cmty.txt.gz    DBLP communities                               
% com-dblp.top5000.cmty.txt.gz    DBLP communities (Top 5,000)               
%                                                                            
% ---------------------------------------------------------------------------
% Notes on inclusion into the SuiteSparse Matrix Collection, July 2018:      
% ---------------------------------------------------------------------------
%                                                                            
% The graph in the SNAP data set is 0-based, with nodes numbering 0 to       
% 425,956.                                                                   
%                                                                            
% In the SuiteSparse Matrix Collection, Problem.A is the undirected          
% collaboration graph, a matrix of size n-by-n with n=317,080, which is the  
% number of unique author id's appearing in any edge.  Problem.aux.nodeid is 
% a list of the node id's that appear in the SNAP data set.  A(i,j)=1 if the 
% author with nodeid(i) is a coauthor with the author with nodeid(j).        
% The node id's are the same as the SNAP data set (0-based).                 
%                                                                            
% C = Problem.aux.Communities_all is a sparse matrix of size n by 13,477,    
% which represents the 13,477 communities in the com-dblp.all.cmty.txt file. 
% The kth line in that file defines the kth community, and is the column     
% C(:,k), where C(i,k)=1 if author nodeid(i) is in the kth community.  Row   
% C(i,:) and row/column i of the A matrix thus refer to the same author.     
% There are a few duplicate communities in this list with 13,423 unique      
% communities out of 13,477 total.                                           
%                                                                            
% Ctop = Problem.aux.Communities_top5000 is n-by-5000, with the same         
% structure as the C array above.  This list has duplicates, which are       
% preserved here.  There are 4,961 unique communities.                       
%-------------------------------------------------------------------------------
