Clique Graph
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In
graph theory In mathematics and computer science, graph theory is the study of ''graph (discrete mathematics), graphs'', which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of ''Vertex (graph ...
, a clique graph of an
undirected graph In discrete mathematics, particularly in graph theory, a graph is a structure consisting of a set of objects where some pairs of the objects are in some sense "related". The objects are represented by abstractions called '' vertices'' (also call ...
is another graph that represents the structure of
cliques A clique ( AusE, CanE, or ; ), in the social sciences, is a small group of individuals who interact with one another and share similar interests rather than include others. Interacting with cliques is part of normative social development regardle ...
in . Clique graphs were discussed at least as early as 1968, and a characterization of clique graphs was given in 1971.


Formal definition

A clique of a graph ''G'' is a set ''X'' of vertices of ''G'' with the property that every pair of distinct vertices in ''X'' are adjacent in ''G''. A maximal clique of a graph ''G'' is a clique ''X'' of vertices of ''G'', such that there is no clique ''Y'' of vertices of ''G'' that contains all of ''X'' and at least one other vertex. Given a graph ''G'', its clique graph ''K''(''G'') is a graph such that * every vertex of ''K''(''G'') represents a maximal clique of ''G''; and * two vertices of ''K''(''G'') are adjacent when the underlying cliques in ''G'' share at least one vertex in common. That is, the clique graph ''K''(''G'') is the intersection graph of the maximal cliques of ''G''.


Characterization

A graph ''H'' is the clique graph ''K''(''G'') of another graph if and only if there exists a collection ''C'' of cliques in ''H'' whose union covers all the edges of ''H'', such that ''C'' forms a
Helly family In combinatorics, a Helly family of order is a family of Set (mathematics), sets in which every minimal ''subfamily with an empty Intersection (set theory), intersection'' has or fewer sets in it. Equivalently, every finite subfamily such that ...
. This means that, if ''S'' is a subset of ''C'' with the property that every two members of ''S'' have a non-empty intersection, then ''S'' itself should also have a non-empty intersection. However, the cliques in ''C'' do not necessarily have to be maximal cliques. When ''H'' =''K''(''G''), a family ''C'' of this type may be constructed in which each clique in ''C'' corresponds to a vertex ''v'' in ''G'', and consists of the cliques in ''G'' that contain ''v''. These cliques all have ''v'' in their intersection, so they form a clique in ''H''. The family ''C'' constructed in this way has the Helly property, because any subfamily of ''C'' with pairwise nonempty intersections must correspond to a clique in ''G'', which can be extended to a maximal clique that belongs to the intersection of the subfamily. Conversely, when ''H'' has a Helly family ''C'' of its cliques, covering all edges of ''H'', then it is the clique graph ''K''(''G'') for a graph ''G'' whose vertices are the
disjoint union In mathematics, the disjoint union (or discriminated union) A \sqcup B of the sets and is the set formed from the elements of and labelled (indexed) with the name of the set from which they come. So, an element belonging to both and appe ...
of the vertices of ''H'' and the elements of ''C''. This graph ''G'' has an edge for each pair of cliques in ''C'' with nonempty intersection, and for each pair of a vertex of ''H'' and a clique in ''C'' that contains it. However, it does not contain any edges connecting pairs of vertices in ''H''. The maximal cliques in this graph ''G'' each consist of one vertex of ''H'' together with all the cliques in ''C'' that contain it, and their intersection graph is isomorphic to ''H''. However, this characterization does not lead to efficient algorithms: the problem of recognizing whether a given graph is a clique graph is
NP-complete In computational complexity theory, NP-complete problems are the hardest of the problems to which ''solutions'' can be verified ''quickly''. Somewhat more precisely, a problem is NP-complete when: # It is a decision problem, meaning that for any ...
.


References

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External links


Information System on Graph Classes and their Inclusions
Graph operations