Networks derive their value by delivering the right information at the right time, to the right places via the right mode.
Essential to achieving this is the capability to abstract, categorize, or otherwise represent characteristics associated with information, the context in which that information is consumed, and the related elements of networks over which that information flows. Information systems research is a key part of a large number of projects in Nokia Bell Labs.
Alessandra Sala and colleagues are exploring interactive graph-theoretic algorithms for processing large-scale and highly compressed data structures in real time to model how we interact with different families of services and applications. For example, the team has developed a novel methodology to detect the errors of the predicted information spread in a network when only parts of the network are visible.
The team has developed algorithms that quantify how far information spreads in a network when only parts of the network are visible. This calculation depends critically on the underlying topology of the network and the density of hidden nodes.
Marty Reiman and colleagues are designing game theory-based frameworks to gain insights into consumer behaviors when alternative network options associated with content delivery are offered.
An information cascade on an oracle (complete) network and its partially observed counterpart.
Philippe Jacquet and his team are evaluating how network-based functions can supplement data search methods, including the use of fast text analysis methods to identify primary nodes within networks associated with highly dynamic information flow patterns.