NADINE

In the past ten years, modern societies have developed enormous communication and social networks.Their classification and information retrieval becomes a formidable task for the society. Various search solutions have been developed by private companies which are actively used by Internet users. Due to the recent enormous developmentof World Wide Web and communication networks, new tools and algorithms should be invented to characterize the properties of these networks on a more detailed and precise level. It is also highly important to have new tools to classify and rank enormous amount of network information in a way adapted to internal network structures and characteristics. The project will develop new algorithms to facilitate classification and information retrieval from large directed networks, using newly developed Monte Carlo methods.The Google matrix formed by the links of the network will be analyzed by analytical tools of Stochastic Processes, Random Matrix Theory and quantum chaos and by efficient numerical methods for large matrix diagonalization including the Arnoldi method.

New tools and algorithms produced by the project will create fundamental basis for developers of new types of search and social media services, which will put Europe on leading positions in this important area dominated at present by other countries. NADINE tools will find applications in modern networks, including mobile communication networks which will play more and more important role in future. New characterization of complex networks will allow stakeholders to manage information extraction for social networks, communication and other networks in an efficient and rapid way. The project will create efficient voting systems in social networks that will pave the way for new types of democracy solutions in societies at a high communication level.

The consortium is led by CNRS with Universities of Twente and Milan as further partners. The prime role of the Informatics Laboratory is to develop methods suitable and scalable for real world networks as well as contribute to the research of all partners.