Ant behaviour inspires social network search engine
The SoSACO algorithm - based on ants’ behaviour - accelerates the search for routes between two nodes
Researchers at Madrid’s Carlos III University have developed an algorithm based on ant behaviour which they believe can accelerate the search for relationships among elements present in social media networks.
The SoSACO algorithm is based on ants’ behaviour when searching for food, and accelerates the search for routes between two nodes on a graph that represents a social network. SoSACO’s methodology is informed by behaviour that has been perfected by this most disciplined of insect species when its members set out to find nourishment.
In general terms, SoSACO models itself on the algorithms used by colonies of ants, and imitates how they are capable of finding the path between the anthill and the source of food by secreting and following a chemical trail, called a pheromone, which is deposited on the ground.
In SoSACO study other scented trails are also included so that the ants can follow both the pheromone as well as the scent of the food, which allows them to locate the food source more quickly. The system can find these associated routes more easily, researchers say, without modifying the structure of the graph (an image that uses nodes and links to represents the relationships among a set of elements).
The results could be applied to anything that can be modelled in a graph of this kind, for example to find routes in online games, to plan freight deliveries, to know if two words are somehow related or to simply know exactly which affinities two Facebook or Twitter users, for example, have in common.
Jessica Rivero, who carried out the research as part of her doctoral thesis, said: “The early results show that the application of this algorithm to real social networks obtains an optimal response in a very short time (tens of milliseconds).”
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