Large graphs are often used to simulate and model complex systems in various research
and application fields. Because of its importance, frequent subgraph mining (FSM) in single …

Weighted single large graphs are often used to simulate complex systems, and thus mining
frequent subgraphs in a weighted large graph is an important issue that has attracted the …

Transactional frequent subgraph mining identifies frequent structural patterns in a collection
of graphs. This research problem has wide applicability and increasingly requires higher …

The accelerated urbanization process has raised higher demands for urban planning and
management, and a precise understanding of urban spatial interaction characteristics is …

The theory of network reliability has been applied to many complicated network structures,
such as computer and communication networks, pi** systems, electricity networks, and …

Knowledge mining from graph data has attracted many researchers over the past several
years. With the evolution of internet, computer technology, social networking sites, and web …

Frequent subgraph mining is an important topic of graph mining, which has practical
applications in many areas such as web link analysis, molecular substructure explorer, fraud …

El enfoque GQM (Meta-Pregunta-Métrica, por sus siglas en inglés) ha sido utilizado en el
proceso de evaluación de calidad de productos de software, como instancia de un …

Now a days people find social networks as an effective means of communication and
interaction. Therefore, it is beneficial to analyse the information from these social networks to …

Frequent pattern mining is a core problem in data mining. Algorithms for frequent pattern
mining have been proposed for itemsets, sequences, and graphs. However, existing graph …