AGIR: Automating Cyber Threat Intelligence Reporting with Natural Language Generation

Cyber Threat Intelligence (CTI) reporting is pivotal in contemporary risk management strategies. As the volume of CTI reports continues to surge, the demand for automated tools to streamline report generation becomes increasingly apparent. While Natural Language Processing techniques have shown potential in handling text data, they often...

Automatic generation of anomaly reports in a Train Control System: Using Natural Language Generation and Case-Based Reasoning

In this thesis, we study automatically generating explanatory reports for anomalous incidents in a train control system (TCS) using Natural Language Generation (NLG). A TCS is a type of safety-critical software that allows train controllers to correctly set the tracks for a train to pass. The goal of this research is to process the majority of...

Correspondence Between Perplexity Scores and Human Evaluation of Generated TV-Show Scripts

In recent years many new text generation models have been developed while evaluation of text generation remains a considerable challenge.  Currently, the only metric that is able to fully capture the quality of a generated text is human evaluation, which is expensive and time consuming. One of the most used intrinsic...

From log files to train traffic reports : Using Natural Language Generation to explain anomalies from Train Control System log files

The Natural Language Generation field has advanced in generating human readable reports for domain experts in various fields. Nevertheless, Natural Language Generation and anomaly detection techniques have not been used in the rail domain yet. Currently, data analysis and incident reporting for log files from the train control system are...