Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning
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 previ...
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| Veröffentlicht in: | International journal of advanced computer science & applications 2023, Vol.14 (9) |
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| container_issue | 9 |
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| container_title | International journal of advanced computer science & applications |
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| creator | Alam, Md. Safiul Roy, Anirban Majumder, Partha Protim Khushbu, Sharun Akter |
| description | 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. |
| doi_str_mv | 10.14569/IJACSA.2023.0140976 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 2158-107X |
| ispartof | International journal of advanced computer science & applications, 2023, Vol.14 (9) |
| issn | 2158-107X 2156-5570 |
| language | eng |
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| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Algorithms Artificial intelligence Bullying Computer science Cybersecurity Data mining Internet Internet access Internet service providers Machine learning Safety Virtual communities |
| title | Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning |
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