Deep Neural Network-Based Approach to Classification the Crime Related News Posts

dc.contributor.author	Sandagiri, S.P.C.W
dc.date.accessioned	2021-07-02T07:10:16Z
dc.date.available	2021-07-02T07:10:16Z
dc.date.issued	2021-02-24
dc.identifier.issn	2773-7136
dc.identifier.uri	http://repo.lib.sab.ac.lk:8080/xmlui/handle/123456789/1737
dc.description.abstract	Crime is a major problem faced today by society. Crimes have affected the quality of life and economic growth badly. We can identify the crime patterns and predict the crimes by detecting and analyzing the historical data. However, some crimes are unregistered and unsolved due to a lack of evidence. Researchers used different sources to get crimes related data to generate the prediction model. But, some crimes are unregistered. In this paper, we used online news posts to detect crimes. crimes. As the first step, we fetch the news posts using predefined keywords relating to the crimes. Then, we proposed the Long short-term memory (LSTM) approach to the classification of crime types and non-crime related posts. Our approach outperformed the existing approaches by obtaining 88.4% accuracy.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computing and Information Systems, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, P.O. Box 02, Belihuloya, 70140, Sri Lanka.	en_US
dc.subject	Crime detection	en_US
dc.subject	Online news	en_US
dc.subject	LSTM	en_US
dc.subject	GloVe	en_US
dc.title	Deep Neural Network-Based Approach to Classification the Crime Related News Posts	en_US
dc.type	Article	en_US