The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices
whose induced subgraph maximizes a measure of density. The problem has received a …

This newly expanded and updated second edition of the best-selling classic continues to
take the" mystery" out of designing algorithms, and analyzing their efficacy and efficiency …

'Network'is a heavily overloaded term, so that 'network analysis' means different things to
different people. Specific forms of network analysis are used in the study of diverse …

A lot of research in graph mining has been devoted in the discovery of communities. Most of
the work has focused in the scenario where communities need to be discovered with only …

Finding dense subgraphs is an important graph-mining task with many applications. Given
that the direct optimization of edge density is not meaningful, as even a single edge …

We study the problem of finding highly connected subgraphs of undirected and directed
graphs. For undirected graphs, the notion of density of a subgraph we use is the average …

Numerous graph mining applications rely on detecting subgraphs which are large near-
cliques. Since formulations that are geared towards finding large near-cliques are hard and …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

Algorithmica Page 1 DOI: 10.1007/s004530010050 Algorithmica (2001) 29: 410–421
Algorithmica © 2001 Springer-Verlag New York Inc. The Dense k-Subgraph Problem1 U …

The use of static graphs for modelling and analysis of biological and biomedical data plays a
key role in biomedical research. However, many real-world scenarios present dynamic …