We define a general variant of the graph clustering problem where the criterion of density for the clusters is (high) connectivity. In Clustering to Given Connectivities, we are given an n-vertex graph G, an integer k, and a sequence Λ = ⟨λ1, . . . , λt⟩ of positive integers and we ask whether it is possible to remove at most k edges from G such that the resulting connected components are exactly t and their corresponding edge connectivities are lower-bounded by the numbers in Λ. We prove that this problem, parameterized by k, is fixed parameter tractable, i.e., can be solved by an f(k) ⋅ n O(1) -step algorithm, for some function f that depends only on the parameter k. Our algorithm uses the recursive understanding technique that is especia...
We consider the following clustering problem: we have a complete graph on vertices (items), where e...
We present efficient fixed-parameter algorithms for the NP-complete edge modification problems Clust...
Abstract. A popular way of formalizing clusters in networks are highly connected subgraphs, that is,...
We define a general variant of the graph clustering problem where the criterion of density for the c...
We define a general variant of the graph clustering problem where the criterion of density for the c...
We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given...
AbstractThe Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit...
In the family of clustering problems we are given a set of objects (vertices of the graph), together...
The CORRELATION CLUSTERING problem, also known as the CLUSTER EDITING problem, seeks to edit a given...
This paper deals with graph clustering algorithm which partitions a set of vertices in graphs into s...
We address a collection of related connectivity and cut problems in simple graphs that reach from th...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
We consider the following clustering problem: we have a complete graph on vertices (items), where e...
We present efficient fixed-parameter algorithms for the NP-complete edge modification problems Clust...
Abstract. A popular way of formalizing clusters in networks are highly connected subgraphs, that is,...
We define a general variant of the graph clustering problem where the criterion of density for the c...
We define a general variant of the graph clustering problem where the criterion of density for the c...
We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given...
AbstractThe Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit...
In the family of clustering problems we are given a set of objects (vertices of the graph), together...
The CORRELATION CLUSTERING problem, also known as the CLUSTER EDITING problem, seeks to edit a given...
This paper deals with graph clustering algorithm which partitions a set of vertices in graphs into s...
We address a collection of related connectivity and cut problems in simple graphs that reach from th...
In the Correlation Clustering problem, also known as Cluster Editing, we are given an undirected gra...
We consider the following clustering problem: we have a complete graph on vertices (items), where e...
We present efficient fixed-parameter algorithms for the NP-complete edge modification problems Clust...
Abstract. A popular way of formalizing clusters in networks are highly connected subgraphs, that is,...