Abstract: A computing system accesses crime incident data from two or more organization systems. The crime incident data includes a first set of inputs associated with a plurality of crime incident groupings and a second set of inputs associated with incident data for incidents associated with each of the two or more organization systems. The computing system preprocesses the crime incident data to remove incidents that include suspect identifiers not present in at least two or more organization system. The computing system analyzes the preprocessed crime incident data to identify links between incidents across two or more organization systems using a trained crime linking model. The computing system generates a link between a first incident at a first organization system of the two or more organization systems and a second incident at a second organization system based on the analyzing.

Abstract: A method for automatically linking associated incidents related to criminal activity is disclosed. A system for processing the method is also disclosed. The method operates by scraping text from a number of incident reports. The scraped text is then analyzed to determine the present of one or more unique IDs, which are used to calculate similarity between each incident report. The system employs machine-learning to better identify these pairs in the future, and optionally with the assistance of a human user providing a feedback loop to enhance the machine-learning.