Social interactions that occur regularly typically correspond to significant yet often infrequent
and hard to detect interaction patterns. To identify such regular behavior, we propose a new …

In systems of interacting entities such as social networks, interactions that occur regularly
typically correspond to significant, yet often infrequent and hard to detect, interaction …

Graph-structured data is becoming increasingly abundant in many application domains.
Graph mining aims at finding interesting patterns within this data that represent novel …

Dynamic graphs are used to represent relationships between entities that evolve over time.
Meaningful patterns in such structured data must capture strong interactions and their …

With an increasing interest in social network applications, finding frequent social interactions
can help us to do disease modeling, cultural and information transmission and behavioral …

The recent proliferation of graph data in a wide spectrum of applications has led to an
increasing demand for advanced data analysis techniques. In view of this, many graph …

Networks from different genres are not static entities, but exhibit dynamic behavior. The
congestion level of links in transportation networks varies in time depending on the traffic …

Many graphs in real-world applications, such as telecommunications networks, social-
interaction graphs and co-authorship graphs, contain temporal information. However …

As data mining techniques are being increasingly applied to non-traditional domains,
existing approaches for finding frequent itemsets cannot be used as they cannot model the …

In recent years, social media have become a useful tool to stay in contact with friends, to
share thoughts but also to be informed about events. Users can follow news channels, but …