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 …

Abstract Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical
ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental …

We develop new methods based on graph motifs for graph clustering, allowing more
efficient detection of communities within networks. We focus on triangles within graphs, but …

Recently, community search over graphs has attracted significant attention and many
algorithms have been developed for finding dense subgraphs from large graphs that contain …

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 …

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 …

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 …

Benford's law describes the distribution of the first digit of numbers appearing in a wide
variety of numerical data, including tax records, and election outcomes, and has been used …

This paper considers the sparse eigenvalue problem, which is to extract dominant (largest)
sparse eigenvectors with at most k non-zero components. We propose a simple yet effective …

The densest subgraph problem in a graph (DSG), in the simplest form, is the following.
Given an undirected graph G=(V, E) find a subset S⊆ V of vertices that maximizes the ratio …