Identification of Criminals based on Criminal Behavioral Similarity Patterns using Series Finder and Prefix Span Algorithm

This research automatically detects patterns of criminal behavior similarity. It can be difficult to identify which of the many crimes that occur in a city each year were perpetrated by the same offender. In order to more accurately attribute previous crimes and apprehend individuals, these strategies may aid law enforcement in understanding crime patterns. All of this would be achievable if analysts had access to automated, data-driven techniques for detecting crime patterns. To achieve this, we propose the Series Finder, Prefix Span algorithm, which develops a pattern to find crimes from a dataset, starting with a seed of the algorithm. This algorithm takes care of predictive analytics, geographic profiling, crime mapping, modus operandi analysis, link analysis, intelligence and information sharing, behavioral analysis profiling and pattern recognition.