Open AccessUsing Mapreduce Techniques to Predict and Examine Crime Pattern
Author(s) -
Anushka Kumar,
S Vishnudas,
R Kayalvizhi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.12.15860
Subject(s) - schema (genetic algorithms) , computer science , listing (finance) , big data , crime analysis , computer security , organised crime , set (abstract data type) , data science , criminology , data mining , information retrieval , business , psychology , programming language , finance
The evolution of computer structures and networks has created an alternative set for crook acts, extensively known as the crime. Crime incidents occurrences of specific criminal offenses lead to a heavy risk to the world economy, protection, and well-being of society. This paper provides complete information of crime incidents and their corresponding offenses combining a sequence of strategies in line with the appropriate literature. Initially, this paper evaluates and identifies the alternatives to crime incidents, their individual components and proposes a combinatorial incident-description schema. The schema offers the chance to systematically blend various elements or crime traits. Moreover, a complete listing of crime-associated offenses is provided in this paper. So, to increase the performance of crime detection, it is essential to choose the data mining strategies appropriately. Hadoop enables to solve the crime as a radical expertise of the repetition and underlying criminal activities. Using Hadoop, we can locate the specific city and analyze the crime patterns, based on that give preventive measures to people.