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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 WallaceDrawings 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 ConferencePagination
105 - 112Publisher
Institute of Electrical and Electronics EngineersLocation
Yokohama, JapanPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2014-03-04End date
2014-03-07ISSN
2165-8765eISSN
2165-8773ISBN-13
9781479928736Language
engPublication classification
E Conference publication; E1.1 Full written paper - refereedCopyright notice
2014, IEEEEditor/Contributor(s)
L O'ConnerTitle of proceedings
PacificVic 2014 : Proceedings of the 2014 IEEE Pacific Visualization SymposiumUsage metrics
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