Abstract—Networks are used in many research domains to model the relationships between entities. We present a publicly available toolkit to extract graphs from datasets or data streams and to analyse their properties. The graph extraction is based on a set of rules that define the links between entities in a set or stream of self-contained events involving sets of entities. As the extracted graph is dynamic and, moreover, can be spread over multiple machines, we include the class of gossip algorithms to analyse them. In addition, the toolkit also contains algorithms to compute metrics of static snapshots of the dynamic graph. I
The analysis of dynamic systems provides insights into their time-dependent characteristics. This en...
International audienceStream graphs are a very useful mode of representation for temporal network da...
In this thesis, the focus is on data that has network structure and on problems that benefit from th...
With the rise of online social networks and other highly dynamic system, the need for the analysis o...
The rapid increase in connected data from various sources such as the World Wide Web, social network...
The ever-expanding demands for network utilities today have greatly changed people’s lives. We are a...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data stream...
A graph is a versatile data structure facilitating representation of interactions among objects in v...
Every day, millions of customers of mobile phone operators communicate via phone calls, SMS or MMS. ...
How can we find communities in dynamic networks of social interactions, such as who calls whom, who ...
A dynamic network is a special type of network composed of connected transactors which have repeated...
Network data are produced automatically by everyday interactions — social networks, power grids, and...
To facilitate the analysis of real and simulated data on groups, organizations and societies, tools ...
Network analysis and graph mining play a prominent role in providing insights and studying phenomena...
Dynamic graphs are ubiquitous in real world applications. They can be found, e.g. in biology, neuros...
The analysis of dynamic systems provides insights into their time-dependent characteristics. This en...
International audienceStream graphs are a very useful mode of representation for temporal network da...
In this thesis, the focus is on data that has network structure and on problems that benefit from th...
With the rise of online social networks and other highly dynamic system, the need for the analysis o...
The rapid increase in connected data from various sources such as the World Wide Web, social network...
The ever-expanding demands for network utilities today have greatly changed people’s lives. We are a...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data stream...
A graph is a versatile data structure facilitating representation of interactions among objects in v...
Every day, millions of customers of mobile phone operators communicate via phone calls, SMS or MMS. ...
How can we find communities in dynamic networks of social interactions, such as who calls whom, who ...
A dynamic network is a special type of network composed of connected transactors which have repeated...
Network data are produced automatically by everyday interactions — social networks, power grids, and...
To facilitate the analysis of real and simulated data on groups, organizations and societies, tools ...
Network analysis and graph mining play a prominent role in providing insights and studying phenomena...
Dynamic graphs are ubiquitous in real world applications. They can be found, e.g. in biology, neuros...
The analysis of dynamic systems provides insights into their time-dependent characteristics. This en...
International audienceStream graphs are a very useful mode of representation for temporal network da...
In this thesis, the focus is on data that has network structure and on problems that benefit from th...