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 …

Graph partitioning is an effective way to improve the performance of parallel computing.
However, the research of graph partitioning is driven by the demand of practical …

Mining change patterns can give unique understanding on the evolution of dynamically
changing systems like social relation graphs, weblinks, hardware descriptions and models …

The increasing number of connected devices to provide the required ubiquitousness of
Internet of Things and the massive machine-type communications of 5G and beyond pave …

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 …

Frequent subgraph mining (FSM) is a subsection of graph mining domain which is
extensively used for graph classification and graph clustering purposes. Over the past …

Software has found its way into many aspects of our everyday lives. However, the actual
development of software is known to be time-consuming, and even minor mistakes can lead …

The increasing number of connected devices to provide the required ubiquitousness of
Internet of Things paves the way for distributed network attacks at an unprecedented scale …

In this paper the authors have used a systematic literature review to provide benchmarking
on influencing parameters for graph partitioning tools, which is the principal contribution of …