Combinatorial Network Abstraction by Trees and Distances

نویسندگان

  • Stefan Eckhardt
  • Sven Kosub
  • Moritz G. Maaß
  • Hanjo Täubig
  • Sebastian Wernicke
چکیده

We draw attention to network abstraction as a fundamental problem within network analysis and visualization. A combinatorial network abstraction problem is specified by a class P of pattern graphs and a real-valued similarity measure % based on certain graph properties. For fixed P and %, the optimization task on any graph G is finding a subgraph G′ which belongs to P such that %(G,G′) is minimal. In this work, we consider this problem for the natural case of trees (as the class of pattern graphs) and similarity-measures based on distances. In particular—with respect to the most standard vector and matrix norms—we systematically study sub-trees of graphs that minimize distances, approximate distances, and approximate closeness-centrality.Although these similarity measures lead to reasonable results, the complexity analysis of finding optimal trees is discouraging: we prove that all problems are NP-complete independent of the norms used, except for the case of minimizing distances with respect to the L∞ matrix-norm which was already known to have a polynomial algorithm.

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تاریخ انتشار 2005