DIMACS10/preferentialAttachment
DIMACS10 set: clustering/preferentialAttachment
| Name | preferentialAttachment | 
| Group | DIMACS10 | 
| Matrix ID | 2575 | 
| Num Rows | 100,000 | 
| Num Cols | 100,000 | 
| Nonzeros | 999,970 | 
| Pattern Entries | 999,970 | 
| Kind | Random Undirected Graph | 
| Symmetric | Yes | 
| Date | 2011 | 
| Author | H. Meyerhenke | 
| Editor | H. Meyerhenke | 
 
 
| Structural Rank |  | 
| Structural Rank Full |  | 
| Num Dmperm Blocks |  | 
| Strongly Connect Components | 1 | 
| Num Explicit Zeros | 0 | 
| Pattern Symmetry | 100% | 
| Numeric Symmetry | 100% | 
| Cholesky Candidate | no | 
| Positive Definite | no | 
| Type | binary | 
 
 
| Download | MATLAB
Rutherford Boeing
Matrix Market | 
| Notes | 
DIMACS10 set: clustering/preferentialAttachment                    
source: http://www.cc.gatech.edu/dimacs10/archive/clustering.shtml 
                                                                   
This graph has been generated following a preferential attachment  
process (see Barabási and Albert, "Emergence of scaling in random  
networks", Science, 1999). Starting with a clique of five vertices,
the vertices are successively added to the graph. Each new vertex  
chooses exactly five neighbors among the existing vertices, such   
that the probability of choosing a particular vertex is            
proportional to its degree. In our implementation, a vertex can    
choose a neighbour only once, such that the resulting random graph 
is guaranteed to be simple. |