Regularity lemmas for clustering graphs
Introduction
One of the celebrated results of Szemerédi [19] is the so-called regularity lemma which asserts that for any graph on n vertices, the vertex set can be partitioned into finitely many parts so that almost all but edges are contained in the union of bipartite subgraphs between pairs of the parts that are random-like under the notion of ϵ-regular. A bipartite graph is said to be ϵ-regular, if the edge density on any induced sub-bipartite graph on at least ϵn vertices differs from the edge density of the bipartite graph by at most ϵ. The regularity lemma has been a powerful tool in graph theory with numerous applications [11], [14], [17] because any graph (with more than edges) can be approximated by a finite graph in the sense that each vertex of the finite graph can be replaced by a subset of vertices and the bipartite subgraphs between any two subsets are quasirandom.
A major deficiency of the regularity lemma is the fact that it is useful only for graphs with a positive edge density since the error bound of approximation is of order . There have been numerous attempts for possible extensions of the regularity lemma to sparse graphs, mostly with either additional assumptions [13] or weakened conditions [9], [18].
In this paper, we give a regularity lemma for clustering graphs without any restriction on edge density. We note that many information networks and social network graphs contain a large number of triangles and thus have nontrivial clustering coefficients [16], [20]. Such a clustering effect is one of the main characteristics of the so-called “small world phenomenon” that appear in a variety of real world graphs [15]. There are many research papers concerning finding dense subgraphs [2], [3] or partitioning into dense clique-like subgraphs [12] for such small-world graphs.
In this paper, we focus on graphs with nontrivial clustering coefficients (or triangle density). Let denote the number of triangles in G and denote the number of paths of two edges. The clustering coefficient is defined to be (see [16]) If , we define . We say G is a clustering graph if its clustering coefficient is a positive constant independent of the number of vertices of G.
Theorem 1 For any and any graph G with clustering coefficient C, the vertex set of G can be partitioned into for some m depending only on ϵ and C, such that all but triangles in G are contained in the projections of tripartite subgraphs with vertex set that are ϵ-Δ-regular.
The detailed definitions of various terms above will be given in Section 2. The proof of the regularity lemma for clustering graphs are quite similar to the previous proofs for the original regularity lemma [4], [14], [19] except for using an index function involving clustering coefficients. In Section 3 we give a proof of the regularity lemma for tripartite graphs with nontrivial clustering coefficient. The proof is self-contained and relatively short. In Section 4 we then consider a strong version of ϵ-Δ-regular for tripartite graphs. In Section 5 we give a proof of Theorem 1 and a weighted version of the regularity lemma both of which are straightforward applications of the regularity lemma for tripartite graphs with nontrivial clustering coefficients. In Section 6, we consider several generalizations of the regularity lemma. We will give a regularity for graphs which is dense in 4-cycles and, in general, graphs which contain a relatively large number of any specified graph (in comparison with its subgraphs). Some remarks and problems are mentioned in Section 7.
Section snippets
Preliminaries
We consider a tripartite graph with the vertex set as the disjoint union . Any triangle in has one vertex in each for . Let denote the number of triangles in . Let denote the number of triples with and are edges in . The clustering coefficient of a tripartite graph is defined to be
For a graph , it is helpful to consider the associated tripartite graph which has vertex set as the disjoint union where is a
A regularity lemma for tripartite graphs
We first prove the following version of the regularity lemma for tripartite clustering graphs. Theorem 2 For any and any tripartite graph with clustering coefficient c, the vertex set of can be partitioned into for some m depending only on ϵ and c, such that all but triangles in are contained in the ϵ-Δ-regular tripartite subgraphs with vertex set . Proof For a partition consisting of partitions of , for , we define the index function :
A strong regularity lemma for tripartite graphs
For a tripartite graph with vertex set , we consider some variations of clustering coefficient. Recall that For , we say a tripartite graph with vertex set is ϵ--regular if for any for , with , we have
We say a tripartite graph with vertex set is strongly ϵ
Regularity lemmas for triangle-dense graphs
In a graph , we consider the associated tripartite graph , where 's are copies of V. For any three subsets , not necessarily distinct, we consider the associated induced subgraph of , denoted by , where is the copy of in . For a triple where , we note that form a triangle in G if and only if forms a triangle in . In other words, the set of triangles in are in one-to-one correspondence with
Several regularity lemmas for general clustering graphs
Many information networks are bipartite and therefore do not have nontrivial clustering coefficient as defined in (1). Nevertheless, some of these graphs contain a relatively large number of 4-cycles . For a graph G, we can define the -clustering coefficient of G, defined by where denotes the number of subgraph of G isomorphic to H. The usual clustering coefficient is just .
Before we define ϵ--regular, we consider the 4-partite graph with vertex set
Problems and remarks
A natural question is to derive a reasonable upper bound for the size of the ϵ-Δ-regular partition for clustering graphs. A crude upper bound as mentioned in the proof of Theorem 1 is of tower type, namely, a tower of 2's of height proportional to where C is the clustering coefficient and ϵ is the desired accuracy. For the original regularity lemma, Gowers [10] gave a lower bound for the size of the partition as a tower of 2's of height . With a slightly different definition of
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