Introduction to algorithms
A distance between isomorphism classes of trees
Czechoslovak Mathematical Journal
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Handbook of Graphs and Networks: From the Genome to the Internet
Handbook of Graphs and Networks: From the Genome to the Internet
Graph decompositions with application to wavelength add-drop multiplexing for minimizing SONET ADMs
Discrete Mathematics - Papers on the occasion of the 65th birthday of Alex Rosa
Network Optimization Using Evolutionary Strategies
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Cyclic pattern kernels for predictive graph mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
A NOVEL METHOD FOR MEASURING THE STRUCTURAL INFORMATION CONTENT OF NETWORKS
Cybernetics and Systems
Towards logical hypertext structure
IICS'04 Proceedings of the 4th international conference on Innovative Internet Community Systems
Brief Communication: Graphs with maximum connectivity index
Computational Biology and Chemistry
A history of graph entropy measures
Information Sciences: an International Journal
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In this article, we present information-theoretic concepts for analyzing complex networks. We see that the application of information-theoretic concepts to networks leads to interesting tasks and gives a possibility for understanding information processing in networks. The main contribution of this article is a method for determining the structural information content of graphs that is based on a tree decomposition. It turns out that the computational complexity of the underlying algorithm is polynomial. Finally, we present some numerical results to study the influence of the used methods on the resulting information contents.