Using the ACO algorithm for path searches in social networks

Authors:
Jessica Rivero;Dolores Cuadra;Javier Calle;Pedro Isasi
Affiliations:
Computer Science Department, Carlos III University of Madrid, Leganés, Spain 28911;Computer Science Department, Carlos III University of Madrid, Leganés, Spain 28911;Computer Science Department, Carlos III University of Madrid, Leganés, Spain 28911;Computer Science Department, Carlos III University of Madrid, Leganés, Spain 28911
Venue:
Applied Intelligence
Year:
2012

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Abstract

One of the most important types of applications currently being used to share knowledge across the Internet are social networks. In addition to their use in social, professional and organizational spheres, social networks are also frequently utilized by researchers in the social sciences, particularly in anthropology and social psychology. In order to obtain information related to a particular social network, analytical techniques are employed to represent the network as a graph, where each node is a distinct member of the network and each edge is a particular type of relationship between members including, for example, kinship or friendship. This article presents a proposal for the efficient solution to one of the most frequently requested services on social networks; namely, taking different types of relationships into account in order to locate a particular member of the network. The solution is based on a biologically-inspired modification of the ant colony optimization algorithm.