Cluster Editing, also known as correlation clustering, is a well-studied graph modification
problem. In this problem, one is given a graph and allowed to perform up to k edge additions …

The paper addresses the well-known cluster edge editing problem. A literature survey of
various cluster editing problems and corresponding solving approaches are presented …

Editing a graph to obtain a disjoint union of s-clubs is one of the models for correlation
clustering, which seeks a partition of the vertex set of a graph so that elements of each …

The academic performance of faculty members, as reflected by their research productivity
and quality, is a crucial factor in determining aninstitution's reputation and ranking. However …

Anomaly detection has been studied and modeled using various methods, mostly statistical
but also combinatorial, including clustering. This paper investigates the utility of using exact …

Clustering a graph when the clusters can overlap can be seen from three different angles:
We may look for cliques that cover the edges of the graph with bounded overlap, we may …

Embedding a high dimensional combinatorial object like tokens in text or nodes in graphs
into a lower dimensional Euclidean space is a form of (lossy) data compression. We will …

The problem Cluster Editing with Vertex Splitting models the task of overlapping community
detection by yielding a cluster graph wherein a vertex of the input graph may be split so that …

In the Cluster Editing problem, sometimes known as (unweighted) Correlation Clustering,
we must insert and delete a minimum number of edges to achieve a graph in which every …

We explore Cluster Editing and its generalization Correlation Clustering with a new
operation called permissive vertex splitting which addresses finding overlapping clusters in …