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Graph summarization methods and applications: A survey
While advances in computing resources have made processing enormous amounts of data
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …
A review on algorithms for maximum clique problems
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 …
subgraph) of maximum cardinality. The MCP is notable for its capability of modeling other …
Attention models in graphs: A survey
Graph-structured data arise naturally in many different application domains. By representing
data as graphs, we can capture entities (ie, nodes) as well as their relationships (ie, edges) …
data as graphs, we can capture entities (ie, nodes) as well as their relationships (ie, edges) …
Truss decomposition in massive networks
J Wang, J Cheng - ar** group attacks by spotting lockstep behavior in social networks
How can web services that depend on user generated content discern fraudulent input by
spammers from legitimate input? In this paper we focus on the social network Facebook and …
spammers from legitimate input? In this paper we focus on the social network Facebook and …
A survey of frequent subgraph mining algorithms
Graph mining is an important research area within the domain of data mining. The field of
study concentrates on the identification of frequent subgraphs within graph data sets. The …
study concentrates on the identification of frequent subgraphs within graph data sets. The …
Clustering attributed graphs: models, measures and methods
Clustering a graph, ie, assigning its nodes to groups, is an important operation whose best
known application is the discovery of communities in social networks. Graph clustering and …
known application is the discovery of communities in social networks. Graph clustering and …
Netprobe: a fast and scalable system for fraud detection in online auction networks
Given a large online network of online auction users and their histories of transactions, how
can we spot anomalies and auction fraud? This paper describes the design and …
can we spot anomalies and auction fraud? This paper describes the design and …
Community detection in multi-layer graphs: A survey
Community detection, also known as graph clustering, has been extensively studied in the
literature. The goal of community detection is to partition vertices in a complex graph into …
literature. The goal of community detection is to partition vertices in a complex graph into …
A survey of algorithms for dense subgraph discovery
In this chapter, we present a survey of algorithms for dense subgraph discovery. The
problem of dense subgraph discovery is closely related to clustering though the two …
problem of dense subgraph discovery is closely related to clustering though the two …