Hierarchical Delay Attribution Classification using Unstructured Text in Train Management Systems

EU directives stipulate a systematic follow-up of train delays. In Sweden, the Swedish Transport Administration registers and assigns an appropriate delay attribution code. However, this delay attribution code is assigned manually, which is a complex task. In this paper, a machine learning-based decision support for assigning delay attribution codes based on event descriptions is investigated. The text is transformed using TF-IDF, and two models, Random Forest and Support Vector Machine, are evaluated against a random uniform classifier and the classification …

administration attribution classification code cs.ai cs.lg decision decision support delay hierarchical machine machine learning management paper support sweden systems text train transport unstructured