Function Prediction
in Complex Networks

July 19-20
University Residential Center
Bertinoro (Forlì-Cesena), Italy

How can we understand, model and control the complex network of interactions which underlie so many systems in the real world? So many systems in the modern world are described by a web of interacting elements. Internet connections, social networks, financial transactions, protein interactions, the spread of disease and ecological networks are just a few such examples. Despite the diversity of the data sources, there are a number of recurring questions which seem largely independent of the data.

The goal of network science is to study the networks of interactions which underlie many complex systems and datasets in science. These networks are ubiquitous in modern science and are used in a very diverse range of fields. A problem falls in the realm of Network Science if it relates to the network itself but is (largely) independent of the data type and is therefore applicable to a wide range of problems.

This meeting aims to bring together researchers from complex networks, and those working in machine learning and graph theory. The goal was to identify current challenges in complex networks analysis and identify possible methodologies for addressing them. The first workshop was held at the Kavli Royal Society Centre, Chicheley Hall, UK in June 2012, and was sponsored by The Royal Society and the PASCAL2 network.

This meeting is organized in conjunction of the International Summer School on Complex Networks held in the Bertinoro Residential center July 14-18 2014