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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of advanced computer science & applications Ročník 14; číslo 9
Hlavní autori: Alam, Md. Safiul, Roy, Anirban, Majumder, Partha Protim, Khushbu, Sharun Akter
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: West Yorkshire Science and Information (SAI) Organization Limited 2023
Predmet:
Algorithms
Artificial intelligence
Bullying
Computer science
Cybersecurity
Data mining
Internet
Internet access
Internet service providers
Machine learning
Safety
Virtual communities
ISSN:2158-107X, 2156-5570
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2023.0140976