Abstract
Community Finding Problems (CFPs) have become very popular in the last years, due to the high number of users that connect everyday to Social Networks (SNs). The goal of these problems is to group the users that compose the SN in several communities, or circles, in such a way similar users belong to the same community, whereas different users are assigned to different communities. Due to the high complexity of this problem, it is common that researchers use heuristic algorithms to perform this task in a reasonable computational time. This paper is focused on the applicability of a novel bio-inspired algorithm to solve CFPs. The selected algorithm is based on the real behaviour of the Japanese Tree Frog, that has been successfully used to colour maps and extract the Maximal Independent Set of a graph.
Antonio Gonzalez-Pardo
Associate Professor
Lecturer at the Computer Science Department. Main research interests are related to Computational Intelligence and Metaheuristics applied to Social Networks Analysis, and the optimization of graph-based problems.