Traversing News with Ant Colony Optimisation and Negative Pheromones

TL;DR

This paper introduces a bio-inspired algorithm using ant colony optimization with negative pheromones to efficiently traverse and organize online news documents, demonstrated on The Guardian's publications.

Contribution

It presents a novel second-order swarm intelligence algorithm incorporating negative pheromones for traversing news documents, inspired by recent biological findings.

Findings

Successfully finds Hamiltonian cycles over news articles

Utilizes negative pheromones to mark unrewarding paths

Demonstrates effectiveness on The Guardian's news corpus

Abstract

The past decade has seen the rapid development of the online newsroom. News published online are the main outlet of news surpassing traditional printed newspapers. This poses challenges to the production and to the consumption of those news. With those many sources of information available it is important to find ways to cluster and organise the documents if one wants to understand this new system. A novel bio inspired approach to the problem of traversing the news is presented. It finds Hamiltonian cycles over documents published by the newspaper The Guardian. A Second Order Swarm Intelligence algorithm based on Ant Colony Optimisation was developed that uses a negative pheromone to mark unrewarding paths with a "no-entry" signal. This approach follows recent findings of negative pheromone usage in real ants.