Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …

Social network based applications have experienced exponential growth in recent years.
One of the reasons for this rise is that this application domain offers a particularly fertile …

Big data has become an important issue for a large number of research areas such as data
mining, machine learning, computational intelligence, information fusion, the semantic Web …

In recent years the unconstrained binary quadratic program (UBQP) has grown in
importance in the field of combinatorial optimization due to its application potential and its …

The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

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 …

In this survey we overview the definitions and methods for graph clustering, that is, finding
sets of “related” vertices in graphs. We review the many definitions for what is a cluster in a …

The maximum clique problem (MCP) is to determine in a graph a clique (ie, a complete
subgraph) of maximum cardinality. The MCP is notable for its capability of modeling other …

'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 …

We present a depth-first search algorithm for generating all maximal cliques of an undirected
graph, in which pruning methods are employed as in the Bron–Kerbosch algorithm. All the …