An End-to-End Framework for Dynamic Crime Profiling of Places
Shailendra Kumar Gupta, Shreyanshu Shekhar, Neeraj Goel, Mukesh Saini

TL;DR
This paper presents an automated, real-time framework that extracts and integrates online news crime data to dynamically profile and visualize crime-prone areas, aiding safety assessments.
Contribution
It introduces an end-to-end system for crime profiling that automates data collection, analysis, and visualization from unstructured online news sources.
Findings
Successfully extracted crime data from over 345,000 news articles.
Generated accurate crime heat maps matching manual ratings.
Demonstrated real-time, dynamic crime profiling capabilities.
Abstract
Much effort is being made to ensure the safety of people. One of the main requirements of travellers and city administrators is to have knowledge of places that are more prone to criminal activities. To rate a place as a potential crime location, it needs the past crime history at that location. Such data is not easily available in the public domain, however, it floats around on the Internet in the form of newspaper and social media posts, in an unstructured manner though. Consequently, a large number of works are reported on extracting crime information from news articles, providing piecemeal solutions to the problem. This chapter complements these works by building an end-to-end framework for crime profiling of any given location/area. It customizes individual components of the framework and provides a Spatio-temporal integration of crime information. It develops an automated…
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Taxonomy
TopicsData Visualization and Analytics · Crime Patterns and Interventions · Cybercrime and Law Enforcement Studies
