With the popularity of graph applications, frequent pattern mining (FPM) has been playing a
significant role in many domains, such as social networks and bioinformatics. However, due …

Frequent pattern mining (FPM) on large graphs has received more and more attention due
to its importance in various applications, including social media analysis. The FPM models …

Graph mining has become a well-established discipline within the domain of data mining. It
has received much interest over the last decade as advances in computer hardware have …

Frequent pattern mining (FPM) has played an important role in many graph domains, such
as bioinformatics and social networks. In this paper, we focus on geo-social graphs, a kind of …

Frequent pattern mining (FPM), whose goal is to identify patterns with appearance
frequencies above a specified support threshold on a large graph, has attracted increasing …

Mining frequent subgraphs is an important issue in graph mining. It is defined as finding all
subgraphs whose occurrences in the dataset are greater than or equal to a given frequency …

As one of the recent interesting areas in data mining, frequent graph pattern (or sub-graphs)
mining was proposed to deal with more complicated data such as graphs. Moreover, in …

Within the graph mining context, frequent subgraph identification plays a key role in
retrieving required information or patterns from the huge amount of data in a short period …

Finding frequent subgraph patterns in a big graph is an important problem with many
applications such as classifying chemical compounds and building indexes to speed up …

We propose a general class of graph-pattern association rules (GPARs) for social network
analysis. Extending association rules for itemsets, GPARs can help us discover associations …