Swarm intelligence based author identification for digital typewritten text

In this study we report our research on learning an accurate and easily interpretable classifier model for authorship classification of typewritten digital texts. For this purpose we use Ant Colony Optimization; a meta-heuristic based on swarm intelligence. Unlike black box type classifiers, the decision making rules produced by the proposed method are understandable by people familiar to the domain and can be easily enhanced with the addition of domain knowledge. Our experimental results show that the method is feasible and more accurate than decision trees.