Research by the Carlos III University of Madrid (UC3M) has made it possible to develop an algorithm called SoSACO for searching in social networks based on the behavior of ants to find food. Details are published in the magazineApplied Intelligence.
One of the main technical issues in the field of social networks, whose use is becoming more and more widespread, consists of locating the reference chain that leads from one person to another, from one node to another. The biggest challenge in this area is the enormous size of these networks and that the response must be quick, since the end user expects results in the shortest possible time. And the solution seems to come from the hand ofSoSACO algorithm, which accelerates the search for paths between two elements belonging to the graph, that is, the representation through nodes and links of the relationships of a social network.
SoSACO’s operation is inspired by the behavior that has been perfected over thousands of years by one of the most disciplined insects on the planet when it comes to foraging. In general,ant colony algorithms mimic how ant colonies are able to find their way between the anthill and the food source, by deposition and monitoring of a chemical trace called a pheromone. “In this study, other odorous traces are also incorporated so that the ants can follow both the pheromone and the aroma of the food, with which they are able to find the food source much more quickly”, the authors clarify. “The first results show that the application of the algorithm to real social networks manages to obtain an optimal response in a very short time (tens of milliseconds)”, indicates Jessica Rivero, co-author of the work.
The system could also be applied to improve the location of the route in GPS systems or online games, for planning the distribution of goods trucks, to find out if two words are related or simply to learn more. accuracy of the affinities that two users of Facebook or Twitter have in common, for example.
