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

dc.contributor.authorAlam, Md. Safiul
dc.contributor.authorRoy, Anirban
dc.contributor.authorMajumder, Partha Protim
dc.contributor.authorKhushbu, Sharun Akter
dc.date.accessioned2024-07-31T09:27:35Z
dc.date.available2024-07-31T09:27:35Z
dc.date.issued2023-01-15
dc.description.abstractAn 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.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13024
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13024
dc.language.isoen_US
dc.publisherScience and Information Ogranization
dc.sourceDIU Institutional Repository
dc.subjectData mining
dc.subjectMachine learning
dc.subjectInternet
dc.titlePredicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning
dc.typeArticle

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