Abstract

Crimes are common social problems that can even affect the quality of life, even the economic growth of a country. Big Data Analytics (BDA) is used for analyzing and identifying different crime patterns, their relations, and the trends within a large amount of crime data. Here, BDA is applied to criminal data in which, data analysis is conducted for the purpose of visualization. Big data analytics and visualization techniques were utilized to analyze crime big data within the different parts of India. Here, we have taken all the states of Indian for analysis, visualization and prediction. The series of operations performed are data collection, data pre-processing, visualization and trends prediction, in which LSTM model is used. The data includes different cases of crimes with in different years and the crimes such as crime against women and children in which, kidnap, murder, rape. The predictive results show that the LSTM perform better than neural network models. Hence, the generated outcomes will benefit for police and law enforcement organizations to clearly understand crime issues and that will help them to track activities, predict the similar incidents, and optimize the decision making process.

Highlights

  • There are several crimes that are happening in our country

  • The predictive model which is based on a neural network Long Short-Term Memory (LSTM), where a small group of attributes are trained, which further enables the prediction of the class label in the validation stage [26, 27]

  • The results showed that LSTM model performed better than traditional neural network models

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Summary

Introduction

There are several crimes that are happening in our country. But many of the people might not be aware of such crimes that are occurring in the different parts of the world. The different operations that are performed for the purpose of crime data analysis are data collection, data pre-processing, visualization and trends prediction. For the entire process we took the crime data that has been occurred in the different parts of our country. This data includes the year wise information about the different crimes. The predictive model which is based on a neural network Long Short-Term Memory (LSTM), where a small group of attributes are trained, which further enables the prediction of the class label in the validation stage [26, 27]. The LSTM model is being widely used and it is preferred more than the other neural network models since it is easier to handle

Crime Data Analysis
Crime Pattern Discovery and Prediction
Proposed Work
Data Collection
Data Preprocessing
Narrative Visualization
Methodology
Performance Evaluation
Conclusion
Full Text
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