Algorithm of Hierarchical Matrix Clusterization and Its Applications

In this article, the problem of hierarchial matrix clusterization is discussed. For this, influence individuals on community was used. The dividing into groups related participants has been solved, an appropriate algorithm for finding most influential agents proposed. Clustering carried out using reducing adjacency a directed graph with nodes representing members social network and edges relationships between them. applications to problems working groups, advertising in networks complex technical systems are considered.