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 …

Graph mining is one of the arms of Data Mining in which voluminous complex data are
represented in the form of graphs and mining is done to infer useful knowledge from them …

Graphs and Trees are non-linear data structures used to organise, model and solve many
real world problems and becoming more popular both in scientific as well as commercial …

The mining of a complete set of frequent subgraphs from labeled graph data has been
studied extensively. Furthermore, much attention has recently been paid to frequent pattern …

Frequent subgraph mining (FSM) is one of the most challenging tasks in graph mining. FSM
consists of applying the data mining algorithms to extract interesting, unexpected, and useful …

Graph mining is a well-established research field, and lately it has drawn in considerable
research communities. It allows to process, analyze, and discover significant knowledge …

Data mining is a popular research area that has been studied by many researchers and
focuses on finding unforeseen and important information in large databases. One of the …

Data mining algorithms are facing the challenge to deal with an increasing number of
complex objects. Graph is a natural data structure used for modeling complex objects …

The mining of social networks entails a high degree of computational complexity. This
complexity is exacerbate when considering longitudinal social network data. To address this …

Frequent subgraph mining is a popular data mining task, which consists of finding all
subgraphs that appear in at least minsup graphs of a graph database. An important …