  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
framework that crawls online news articles, analyzes them, and extracts
relevant information to create a crime knowledge base that gets dynamically
updated in real-time. The crime density can be easily visualized in the form of
a heat map which is generated by the knowledge base. As a case study, it
investigates 345448 news articles published by 6 daily English newspapers
collected for approximately two years. Experimental results show that the crime
profiling matches with the ratings calculated manually by various
organizations.
