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 …

Pattern discovery in geo-spatiotemporal data (such as traffic and weather data) is about
finding patterns of collocation, co-occurrence, cascading, or cause and effect between …

Frequency counting of complex patterns such as subtrees is more challenging than for
simple itemsets and sequences, as the number of possible candidate patterns in a tree is …

The use of non-linear data structures is becoming more and more common in many data
mining scenarios. Trees, in particular, have drawn the attention of researchers as the …

Event logs, as considered in process mining, document a large number of individual process
executions. Moreover, each process execution consists of various executed activities. To …

Due to the inherent flexibilities in both structure and semantics, XML association rules
mining faces few challenges, such as: a more complicated hierarchical data structure and …

Mining frequent subtrees in a database of rooted and labeled trees is an important problem
in many domains, ranging from phylogenetic analysis to biochemistry and from linguistic …

Mining frequent tree patterns has many applications in different areas such as XML data,
bioinformatics and World Wide Web. The crucial step in frequent pattern mining is frequency …

Frequent tree patterns have many practical applications in different domains, such as
Extensible Markup Language mining, Web usage analysis, etc. In this paper, we present …

Non-linear data structures are becoming more and more common in data mining problems.
Trees, in particular, are amenable to efficient mining techniques. In this paper, we introduce …