Open Access   Article Go Back

Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach

Sadhna Sharma1 , Sanjiv Sharma2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-8 , Page no. 137-143, Aug-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i8.137143

Online published on Aug 31, 2019

Copyright © Sadhna Sharma, Sanjiv Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Sadhna Sharma, Sanjiv Sharma, “Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.8, pp.137-143, 2019.

MLA Style Citation: Sadhna Sharma, Sanjiv Sharma "Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach." International Journal of Computer Sciences and Engineering 7.8 (2019): 137-143.

APA Style Citation: Sadhna Sharma, Sanjiv Sharma, (2019). Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach. International Journal of Computer Sciences and Engineering, 7(8), 137-143.

BibTex Style Citation:
@article{Sharma_2019,
author = {Sadhna Sharma, Sanjiv Sharma},
title = {Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2019},
volume = {7},
Issue = {8},
month = {8},
year = {2019},
issn = {2347-2693},
pages = {137-143},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4801},
doi = {https://doi.org/10.26438/ijcse/v7i8.137143}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.137143}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4801
TI - Identification of Accurate Classification Technique for Crime Investigation Using Ensemble Approach
T2 - International Journal of Computer Sciences and Engineering
AU - Sadhna Sharma, Sanjiv Sharma
PY - 2019
DA - 2019/08/31
PB - IJCSE, Indore, INDIA
SP - 137-143
IS - 8
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
361 385 downloads 174 downloads
  
  
           

Abstract

Recently, it`s observed that the crime is increasing across the world very rapidly and some technique is required for analysis of the crime data. Analysis of the crime data can be done through data mining (DM). DM techniques are applied to crime data for predicting features that affect the high crime rate. Using the method of data mining on previously collected data for predicting the features responsible for the crime in a locality or area, the Police Department and the Crimes Record Bureau Police Department may take the required measures to reduce the likelihood of the crime. In the current work, a new machine learning ensemble algorithm is opted for predicting feature that affects a high crime rate. It helps the police and citizens to take necessary and required action in decreasing the crimes rate. The ensemble algorithm can predict more accurate and significant features with higher accuracy and efficiency.

Key-Words / Index Term

Crime investigation, Crime Prediction, Crime Prediction, Data Mining, Ensemble approach

References

[1] OdedMaimon, LiorRokach, “The Data Mining and Knowledge Discovery Handbook”, Springer 2005, Page 6
[2] Han, Jiawei et.al “Data Mining”, Second Edition, Page 285
[3] Mugdha Sharma, “Z-Crime: A Data Mining Tool for the Detection of Suspicious Criminal Activities based on the Decision Tree”, International Conference on Data Mining and Intelligent Computing, pp. 1-6, 2014
[4] Ehab Hamdy, Ammar Adl, Aboul Ella Hassanien, Osman Hegazy and Tai-Hoon Kim, “Criminal Act Detection and Identification Model”, Proceedings of 7 th International Conference on Advanced Communication and Networking, pp. 79-83, 2015
[5] Kaumalee Bogahawatte and Shalinda Adikari, “Intelligent Criminal Identification System”, Proceedings of 8th IEEE International Conference on Computer Science and Education, pp. 633-638, 2013.
[6] Jyoti Agarwal, Renuka Nagpal and Rajni Sehgal, “Crime Analysis using K-Means Clustering”, International Journal of Computer Applications, Vol. 83, No. 4, pp. 1-4, 2013.
[7] Prajakta Yerpude, Vaishnavi Gudur. “Predictive modelling of crime dataset using data mining”. In international journal of data mining & knowledge management process, vol.7, pp.43-58, 2017.
[8] Jeroen S. De Bruin, Tim K. Cocx, Walter A. Kosters, Jeroen F. J. Laros and Joost N. Kok, “Data Mining Approaches to Criminal Career Analysis”, Proceedings of 6 th IEEE International Conference on Data Mining, pp. 1-7, 2006.
[9] H. Chen, W. Chung, J.J. Xu, G. Wang, Y. Qin and M. Chau, “Crime Data Mining: a General Framework and Some Examples”, Computer, Vol. 37, No. 4, pp. 50-56, 2004.
[10] Sadhna shrama, sanjiv sharma, “ a compartive study of crime investigation using data mining approaches”, International Journal for Research in Applied Science & Engineering Technology,Vol.7,pp. 2073-2079,2019.