Linearity is strictly more powerful than contiguity for encoding graphs

@article{Crespelle2016LinearityIS,
  title={Linearity is strictly more powerful than contiguity for encoding graphs},
  author={Christophe Crespelle and T. Le and K. Perrot and T. Phan},
  journal={ArXiv},
  year={2016},
  volume={abs/1803.05414}
}
  • Christophe Crespelle, T. Le, +1 author T. Phan
  • Published 2016
  • Computer Science, Mathematics
  • ArXiv
  • Linearity and contiguity are two parameters devoted to graph encoding. Linearity is a generalization of contiguity in the sense that every encoding achieving contiguity k induces an encoding achieving linearity k , both encoding having size ? ( k . n ) , where n is the number of vertices of G . In this paper, we prove that linearity is a strictly more powerful encoding than contiguity, i.e. there exists some graph family such that the linearity is asymptotically negligible in front of the… CONTINUE READING

    Figures and Topics from this paper.

    Explore Further: Topics Discussed in This Paper

    Linearity Is Strictly More Powerful Than Contiguity for Encoding Graphs
    1
    Structures of Complex Networks and of their Dynamics
    2

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 17 REFERENCES
    Linearity Is Strictly More Powerful Than Contiguity for Encoding Graphs
    1
    Linear-Time Constant-Ratio Approximation Algorithm and Tight Bounds for the Contiguity of Cographs
    3
    Efficient Neighborhood Encoding for Interval Graphs and Permutation Graphs and O(n) Breadth-First Search
    8
    Graph Minor Theory
    39
    Permuting Web and Social Graphs
    31
    Hamiltonicity of regular graphs and blocks of consecutive ones in symmetric matrices
    16
    The Compactness of Interval Routing
    32
    Complement reducible graphs
    638
    Codes for the World Wide Web
    54