With the rapid development of information storage and networking technologies, quintillion
bytes of data are generated every day from social networks, business transactions, sensors …

Real-world graphs are complex to process for performing effective analysis, such as
anomaly detection. However, recently, there have been several research efforts addressing …

Many applications involve stream data with structural dependency, graph representations,
and continuously increasing volumes. For these applications, it is very common that their …

© 2018 International Joint Conferences on Artificial Intelligence. All right reserved. Attributed
network embedding aims to learn a low-dimensional representation for each node of a …

In this paper, we focus on dense graph streams, which can be generated in various
applications ranging from sensor networks to social networks, from bio-informatics to …

The emergence of mining complex networks like social media, sensor networks, and the
world-wide-web has attracted considerable research interest. In a streaming scenario, the …

Privacy concerns on sharing sensitive data across institutions are particularly paramount for
the medical domain, which hinders the research and development of many applications …

The use of mobile devices grows significantly in all situations of day-to-day. The intense
rhythm of the mobile device market has been pushing the use of practical software …

Existing graph classification usually relies on an exhaustive enumeration of substructure
patterns, where the number of substructures expands exponentially wrt with the size of the …

With the emergence of networked data, graph classification has received considerable
interest during the past years. Most approaches to graph classification focus on designing …