INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
In recent times, terrorism has grown exponentially in certain parts of the world. This enormous growth in terrorist activities has made it important to stop terrorism and prevent its spread before it causes damage to human life or property. With developments in technology, the internet has become a medium for spreading terrorism through speeches and videos. Terrorist organisations use the medium of the internet to harm and defame individuals and also promote terrorist activities through web pages that force people to join terrorist organisations and commit crimes on behalf of those organizations. Web mining and data mining are used simultaneously for the purpose of efficient system development. Web mining even consists of many different text mining methods that can be helpful to scan and extract relevant data from unstructured data. Text mining is very helpful in detecting various patterns, keywords, and significant information in unstructured texts. Text mining systems such as data mining and web mining are widely used. Data mining algorithms are used to manage organized.
"A Review of Terrorist Activity Detection Using a Machine Learning Approach", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.601 - 604, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303097.pdf
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Publication Details:
Published Paper ID: IJSDR2303097
Registration ID:204605
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 601 - 604
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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