A study on Elements of Crime Facts and Visualizing the Storyline through Named Entity Recognition and Event Extraction

2022-11-04 seminar review

On November 4th, 2022, there was a thesis presentation by graduate student Yuna Lee at Hallym University in Chuncheon, Gangwon Province.


This paper is a research result supported by the 2022 government (National Police Agency) funding. In this paper, we propose a methodology that utilizes named entity recognition and event extraction techniques suitable for reconstructing criminal cases, presenting a clearer and more simplified visual representation of the storyline. We examine related research on named entity recognition (NER) and event extraction techniques, and provide a system flowchart and examples using actual cases to demonstrate the approach for extracting and visualizing criminal events

To address the above issues in limited environments, this paper proposes a method for analyzing and visually representing criminal facts in legal judgments using named entity recognition and event extraction techniques. As future work, more detailed information extraction elements need to be applied to pre-trained deep learning models to improve accuracy.