Abstract
The need for analyzing the different crime dataset has significantly increased over the past few decades. It is necessary to detect the wide variety of crimes and the corresponding place of occurrences accurately. Government bodies throughout the world maintained Open Data initiatives, which is a large collection of heterogeneous dataset. This enables the government agencies to maintain the law and order of the society. The prime objective of this paper is to analyze the Chicago crime dataset to extract the significant crime information over the years. The proposed analysis is performed to bring out the crime information depending on some predetermined criteria, e.g. total crimes of different types, narcotic crime cases, an offense involving children, analysis of hourly theft cases and location identification where the major theft cases have occurred. The proposed analysis is performed in fully distributed Hadoop cluster. Moreover, we have extracted crucial minuscule statistics on theft-related criminal activities and their latitude or longitude.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
