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Improved optimal and approximate power graph compression for clearer visualisation of dense graphs

conference contribution
posted on 2014-04-14, 00:00 authored by T Dwyer, C Mears, Kerri Morgan, T Niven, K Marriott, M Wallace
Drawings of highly connected (dense) graphs can be very difficult to read. Power Graph Analysis offers an alternate way to draw a graph in which sets of nodes with common neighbours are shown grouped into modules. An edge connected to the module then implies a connection to each member of the module. Thus, the entire graph may be represented with much less clutter and without loss of detail. A recent experimental study has shown that such lossless compression of dense graphs makes it easier to follow paths. However, computing optimal power graphs is difficult. In this paper, we show that computing the optimal power-graph with only one module is NP-hard and therefore likely NP-hard in the general case. We give an ILP model for power graph computation and discuss why ILP and CP techniques are poorly suited to the problem. Instead, we are able to find optimal solutions much more quickly using a custom search method. We also show how to restrict this type of search to allow only limited back-Tracking to provide a heuristic that has better speed and better results than previously known heuristics.

History

Event

IEEE Computer Society. Conference (2014 : Yokohama, Japan)

Series

IEEE Computer Society Conference

Pagination

105 - 112

Publisher

Institute of Electrical and Electronics Engineers

Location

Yokohama, Japan

Place of publication

Piscataway, N.J.

Start date

2014-03-04

End date

2014-03-07

ISSN

2165-8765

eISSN

2165-8773

ISBN-13

9781479928736

Language

eng

Publication classification

E Conference publication; E1.1 Full written paper - refereed

Copyright notice

2014, IEEE

Editor/Contributor(s)

L O'Conner

Title of proceedings

PacificVic 2014 : Proceedings of the 2014 IEEE Pacific Visualization Symposium

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