학술논문

A Framework for Mapping Crime Data on Sociological Hypothesis
Document Type
Conference
Source
2019 IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT and AI (HONET-ICT) Smart Cities: Improving Quality of Life Using ICT & IoT and AI (HONET-ICT), 2019 IEEE 16th International Conference on. :135-139 Oct, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Data mining
Big Data
Social sciences
Strain
Feature extraction
Data models
Clustering algorithms
social criminal theories
mapping of social theories
data mining
crime analysis
Language
ISSN
1949-4106
Abstract
Data is increasing every second now a days. Interesting facts about the societies can be extracted by converting the data into useful information as user generated content helps to reveal the audience’s perception on different social aspects. Crime is a serious concern all over the world because it affects humans and also the environment surrounding them. Social criminal theories help to identify different aspects of humans that cause the person to commit crime. There is a need to identify the hidden patterns and also the relationship between the data and social theories. In this paper, a framework is proposed that maps the crime data on established social criminal theories. A total of 100 cases have been mapped to check the correctness of the solution. This solution can have great impact on the society to counter the problems of increasing crime and understand the reasons of crime, and also help to take the remedial actions. In this paper, we have considered only social criminal theories, in future we will extend this research by elaborating more criminal theories.