Conditional Responsive Exploratory Causal Inference Analysis Visualization System Research

This study analyzes the digital evidence obtained during the criminal investigation process through causal inference analysis and presents it to investigators in a visualized form so that they can see at a glance what the key clues identified during the investigation process are and what causal relationships exist between the key clues from a criminal perspective. This is a visualization software study that helps you understand easily. It refers to inference SW that can verify the causal relationship between ‘evidence-evidence’ or ‘action-evidence’ by extracting digital evidence that can prove the suspect’s actions from the perspective of proving the facts of the crime. In existing SW, the investigator or Rather than manually constructing clue-causal relationships in the form of Node-Edge based on the analyst’s own arbitrary judgment, it presents visualizations using prior knowledge for relationship-based correlation analysis, helping to enable faster and more accurate investigations.