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.
| Published in | International Journal of Data Science and Analysis (Volume 7, Issue 3) |
| DOI | 10.11648/j.ijdsa.20210703.11 |
| Page(s) | 51-59 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Big Data Analytics, Crime Data, Crime Data Analysis, Visualization, Prediction, LSTM
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APA Style
Mufeeda Manengadan, Silpa Nandanan, Neethu Subash. (2021). Crime Data Analysis, Visualization and Prediction Using LSTM. International Journal of Data Science and Analysis, 7(3), 51-59. https://doi.org/10.11648/j.ijdsa.20210703.11
ACS Style
Mufeeda Manengadan; Silpa Nandanan; Neethu Subash. Crime Data Analysis, Visualization and Prediction Using LSTM. Int. J. Data Sci. Anal. 2021, 7(3), 51-59. doi: 10.11648/j.ijdsa.20210703.11
AMA Style
Mufeeda Manengadan, Silpa Nandanan, Neethu Subash. Crime Data Analysis, Visualization and Prediction Using LSTM. Int J Data Sci Anal. 2021;7(3):51-59. doi: 10.11648/j.ijdsa.20210703.11
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Download@article{10.11648/j.ijdsa.20210703.11,
author = {Mufeeda Manengadan and Silpa Nandanan and Neethu Subash},
title = {Crime Data Analysis, Visualization and Prediction Using LSTM},
journal = {International Journal of Data Science and Analysis},
volume = {7},
number = {3},
pages = {51-59},
doi = {10.11648/j.ijdsa.20210703.11},
url = {https://doi.org/10.11648/j.ijdsa.20210703.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20210703.11},
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.},
year = {2021}
}
TY - JOUR T1 - Crime Data Analysis, Visualization and Prediction Using LSTM AU - Mufeeda Manengadan AU - Silpa Nandanan AU - Neethu Subash Y1 - 2021/05/08 PY - 2021 N1 - https://doi.org/10.11648/j.ijdsa.20210703.11 DO - 10.11648/j.ijdsa.20210703.11 T2 - International Journal of Data Science and Analysis JF - International Journal of Data Science and Analysis JO - International Journal of Data Science and Analysis SP - 51 EP - 59 PB - Science Publishing Group SN - 2575-1891 UR - https://doi.org/10.11648/j.ijdsa.20210703.11 AB - 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. VL - 7 IS - 3 ER -
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