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Keywords:

  • entropy;
  • graph entropy;
  • information theory;
  • information measures

Abstract

This article deals with generalized entropies for graphs. These entropies result from applying information measures to a graph using various schemes for defining probability distributions over the elements (e.g., vertices) of the graph. We introduce a new class of generalized measures, develop their properties, compute the measures for selected graphs, and briefly discuss potential applications to classification and clustering problems. © 2011 Wiley Periodicals, Inc. Complexity, 17,45–50, 2011