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Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics

Pallavi 1 , Rajeev Kumar Bedi2 , Sunil Kumar Gupta3

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-1 , Page no. 151-158, Jan-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i1.151158

Online published on Jan 31, 2020

Copyright © Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta . 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.

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IEEE Style Citation: Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta, “Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.1, pp.151-158, 2020.

MLA Style Citation: Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta "Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics." International Journal of Computer Sciences and Engineering 8.1 (2020): 151-158.

APA Style Citation: Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta, (2020). Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics. International Journal of Computer Sciences and Engineering, 8(1), 151-158.

BibTex Style Citation:
@article{Bedi_2020,
author = {Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta},
title = {Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2020},
volume = {8},
Issue = {1},
month = {1},
year = {2020},
issn = {2347-2693},
pages = {151-158},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5014},
doi = {https://doi.org/10.26438/ijcse/v8i1.151158}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i1.151158}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5014
TI - Counter-Terrorism and Crime Detection Using Hybrid Approach of Data Mining, NLP and GEO-Spatial Social Media Analytics
T2 - International Journal of Computer Sciences and Engineering
AU - Pallavi, Rajeev Kumar Bedi, Sunil Kumar Gupta
PY - 2020
DA - 2020/01/31
PB - IJCSE, Indore, INDIA
SP - 151-158
IS - 1
VL - 8
SN - 2347-2693
ER -

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Abstract

Crime, an unlawful act, causes terror and threat to our society and is a major concern for national security as well as international security. However, very negligible work has been done to develop models and methods to hold an active collaboration between counter terrorism and criminal investigation systems. The need is felt to develop a system that collects as well as categorise the data on crimes along with an analysis of crime affected areas identification. In this study, an efficient crime investigation system is proposed in which fuzzy rules and k mean clustering algorithm is employed to identify and detect crime affected region along with showing it on the map. The study of Data Mining and NLP is incorporated for crime detection and prevention with an aim to provide a safer society to live.

Key-Words / Index Term

Counter terrorism; Crime detection; Social Media; Data mining; Geo-Spatial; NLP

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