**Matrix: DIMACS10/preferentialAttachment**

Description: DIMACS10 set: clustering/preferentialAttachment

(undirected graph drawing) |

Matrix properties | |

number of rows | 100,000 |

number of columns | 100,000 |

nonzeros | 999,970 |

# strongly connected comp. | 1 |

explicit zero entries | 0 |

nonzero pattern symmetry | symmetric |

numeric value symmetry | symmetric |

type | binary |

structure | symmetric |

Cholesky candidate? | no |

positive definite? | no |

author | H. Meyerhenke |

editor | H. Meyerhenke |

date | 2011 |

kind | random undirected graph |

2D/3D problem? | no |

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.

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.
*