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.
|