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Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning

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dc.contributor.author Alam, Md. Safiul
dc.contributor.author Roy, Anirban
dc.contributor.author Majumder, Partha Protim
dc.contributor.author Khushbu, Sharun Akter
dc.date.accessioned 2024-07-31T09:27:35Z
dc.date.available 2024-07-31T09:27:35Z
dc.date.issued 2023-01-15
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13024
dc.description.abstract An amazing combination of cutting-edge data mining and machine learning methodologies to predict the level of safety feeling among Bangladeshi internet users, which is a significant departure in this subject. By leveraging cutting-edge algorithms and innovative data sources, this work provides previously unheard-of insights into how this demographic perceives online safety, shedding light on an essential yet underappreciated aspect of their digital lives. This exceptional study's original research increases the body of knowledge of online safety and sets the road for policy recommendations and intervention tactics that will enable Bangladesh to become a global leader in internet security. en_US
dc.language.iso en_US en_US
dc.publisher Science and Information Ogranization en_US
dc.subject Data mining en_US
dc.subject Machine learning en_US
dc.subject Internet en_US
dc.title Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning en_US
dc.type Article en_US


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