Frequent pattern mining (FPM) algorithms are often based on graph isomorphism in order to
identify common pattern occurrences. Recent research works, however, have focused on …

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 …

This paper presents an informal introduction to semirings and their application in
GraphBLAS using Matlab. GraphBLAS is a powerful and versatile tool for working with graph …

Anomaly detection is a relevant research field in online social networks (OSNs), which
detects the abnormal individuals and activities to protect other regular activities of the whole …

This paper proposes a method for automatically monitoring and analyzing the evolution of
complex geographic objects. The objects are modeled as a spatiotemporal graph, which …

In most of the user applications today, the web has become a fundamental information
resource. Mining the graph structural data from a complex source is a difficult process and in …

Nowadays, significant amounts of data are generated across almost all areas such as social
networks and sensor networks, and useful information is retrieved from these data in the …

The frequent subgraphs are the subgraphs which appear in a number, more than or equal to
a user-defined threshold. Many algorithms assume that the apriori based approach yields an …

In this thesis we study subgraph enumeration problems. We provide an extensive literature
review of subgraph enumeration, considering different problems associated to cliques …

The data when modeled as a graph can bring out a lot of useful information. Path finding is
one of the most popular applications of network analysis. As the data evolution speed from …