Network Models of Massive Datasets

Vladimir Boginski, Sergiy Butenko, Panos M. Pardalos

We give a brief overview of the methodology of modeling massive datasets arising in various applications as networks. This approach is often useful for extracting non-trivial information from the datasets by applying standard graph-theoretic techniques. We also point out that graphs representing datasets coming from diverse practical fields have a similar power-law structure, which indicates that the global organization and evolution of massive datasets arising in various spheres of life nowadays follow similar natural principles.