**Matrix: Pajek/HEP-th**

Description: Pajek network: High Energy Physics literature

(bipartite graph drawing) | (graph drawing of A+A') |

Matrix properties | |

number of rows | 27,240 |

number of columns | 27,240 |

nonzeros | 342,437 |

# strongly connected comp. | 19,565 |

explicit zero entries | 0 |

nonzero pattern symmetry | 0% |

numeric value symmetry | 0% |

type | binary |

structure | unsymmetric |

Cholesky candidate? | no |

positive definite? | no |

author | KDD Cup 2003 |

editor | V. Batagelj |

date | 2003 |

kind | directed graph |

2D/3D problem? | no |

Additional fields | size and type |

nodename | full 27240-by-7 |

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/. ------------------------------------------------------------------------------ High Energy Particle Physics (HEP) literature --------------------------------------------- Citation data from KDD Cup 2003, a knowledge discovery and data mining competition held in conjunction with the Ninth Annual ACM SIGKDD Conference. http://www.cs.cornell.edu/projects/kddcup/index.html The Stanford Linear Accelerator Center SPIRES-HEP database has been comprehensively cataloguing the High Energy Particle Physics (HEP) literature online since 1974, and indexes more than 500,000 high-energy physics related articles including their full citation tree. The network contains a citation graph of the hep-th portion of the arXiv. The units names are the arXiv IDs of papers; the relation is X cites Y . Note that revised papers may have updated citations. As such, citations may refer to future papers, i.e. a paper may cite another paper that was publishe after the first paper. Update May 12, 2003 is not included. transformed in Pajek format: V. Batagelj, 26. July 2003 -----

SVD-based statistics: | |

norm(A) | 84.3235 |

min(svd(A)) | 5.59609e-66 |

cond(A) | 1.50683e+67 |

rank(A) | 21,162 |

null space dimension | 6,078 |

full numerical rank? | no |

singular value gap | 1.3948e+08 |

singular values (MAT file): | click here |

SVD method used: | s = svd (full (A)) |

status: | ok |

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.
*