Information entropy metrics have been applied to a wide range of problems that were
abstracted as complex networks. This growing body of research is scattered in multiple …

One of the field in which models of abstraction have been proposed is Artificial Intelligence
(AI). This chapter has two parts: one presents an overview of the formal models, either …

Graph theory [12, 83, 86] is a relatively new branch of mathematics and the main body of
fundamental results dates back to the seminal contribution due to König [111]. Earlier …

We show that numerical approximations of Kolmogorov complexity (K) of graphs and
networks capture some group-theoretic and topological properties of empirical networks …

Proving interrelations between structural graph measures analytically has been intricate.
Generally, relations between structural graph measures describe the interplay between …

In the present work, we study the introduction of a latent interaction index, examining its
impact on the formation and development of complex networks. This index takes into …

Frequent graph mining has been proposed to find interesting patterns (ie, frequent sub-
graphs) from databases composed of graph transaction data, which can effectively express …

Abstract The Characteristic Objects METhod (COMET) is a relatively new, rank reversal free,
a multi-criteria decision-support technique based on fuzzy set theory. The advantages of this …

In this article, we discuss the problem of establishing relations between information
measures for network structures. Two types of entropy based measures namely, the …

The entropy of a graph was first introduced by Rashevsky [1] and Trucco [2] to interpret as
the structural information content of the graph and serve as a complexity measure. In this …