158,446 research outputs found
Canonizing Graphs of Bounded Tree Width in Logspace
Graph canonization is the problem of computing a unique representative, a
canon, from the isomorphism class of a given graph. This implies that two
graphs are isomorphic exactly if their canons are equal. We show that graphs of
bounded tree width can be canonized by logarithmic-space (logspace) algorithms.
This implies that the isomorphism problem for graphs of bounded tree width can
be decided in logspace. In the light of isomorphism for trees being hard for
the complexity class logspace, this makes the ubiquitous class of graphs of
bounded tree width one of the few classes of graphs for which the complexity of
the isomorphism problem has been exactly determined.Comment: 26 page
Hitting forbidden minors: Approximation and Kernelization
We study a general class of problems called F-deletion problems. In an
F-deletion problem, we are asked whether a subset of at most vertices can
be deleted from a graph such that the resulting graph does not contain as a
minor any graph from the family F of forbidden minors.
We obtain a number of algorithmic results on the F-deletion problem when F
contains a planar graph. We give (1) a linear vertex kernel on graphs excluding
-claw , the star with leves, as an induced subgraph, where
is a fixed integer. (2) an approximation algorithm achieving an approximation
ratio of , where is the size of an optimal solution on
general undirected graphs. Finally, we obtain polynomial kernels for the case
when F contains graph as a minor for a fixed integer . The graph
consists of two vertices connected by parallel edges. Even
though this may appear to be a very restricted class of problems it already
encompasses well-studied problems such as {\sc Vertex Cover}, {\sc Feedback
Vertex Set} and Diamond Hitting Set. The generic kernelization algorithm is
based on a non-trivial application of protrusion techniques, previously used
only for problems on topological graph classes
The structure of graphs not admitting a fixed immersion
We present an easy structure theorem for graphs which do not admit an immersion of the complete graph. The theorem motivates the definition of a variation of tree decompositions based on edge cuts instead of vertex cuts which we call tree-cut decompositions. We give a definition for the width of tree-cut decompositions, and using this definition along with the structure theorem for excluded clique immersions, we prove that every graph either has bounded tree-cut width or admits an immersion of a large wall
Isomorphism of graph classes related to the circular-ones property
We give a linear-time algorithm that checks for isomorphism between two 0-1
matrices that obey the circular-ones property. This algorithm leads to
linear-time isomorphism algorithms for related graph classes, including Helly
circular-arc graphs, \Gamma-circular-arc graphs, proper circular-arc graphs and
convex-round graphs.Comment: 25 pages, 9 figure
Performance and scalability of indexed subgraph query processing methods
Graph data management systems have become very popular
as graphs are the natural data model for many applications.
One of the main problems addressed by these systems is subgraph
query processing; i.e., given a query graph, return all
graphs that contain the query. The naive method for processing
such queries is to perform a subgraph isomorphism
test against each graph in the dataset. This obviously does
not scale, as subgraph isomorphism is NP-Complete. Thus,
many indexing methods have been proposed to reduce the
number of candidate graphs that have to underpass the subgraph
isomorphism test. In this paper, we identify a set of
key factors-parameters, that influence the performance of
related methods: namely, the number of nodes per graph,
the graph density, the number of distinct labels, the number
of graphs in the dataset, and the query graph size. We then
conduct comprehensive and systematic experiments that analyze
the sensitivity of the various methods on the values of
the key parameters. Our aims are twofold: first to derive
conclusions about the algorithms’ relative performance, and,
second, to stress-test all algorithms, deriving insights as to
their scalability, and highlight how both performance and
scalability depend on the above factors. We choose six wellestablished
indexing methods, namely Grapes, CT-Index,
GraphGrepSX, gIndex, Tree+∆, and gCode, as representative
approaches of the overall design space, including the
most recent and best performing methods. We report on
their index construction time and index size, and on query
processing performance in terms of time and false positive
ratio. We employ both real and synthetic datasets. Specifi-
cally, four real datasets of different characteristics are used:
AIDS, PDBS, PCM, and PPI. In addition, we generate a
large number of synthetic graph datasets, empowering us to
systematically study the algorithms’ performance and scalability
versus the aforementioned key parameters
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