ArticleInternational journal of environmental research and public health2019
An Ensemble Classifier with Case-Based Reasoning System for Identifying Internet Addiction.
Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Risk level prediction for problematic internet use: A digital health perspective.Internet interventions · 2025Article
- Classification of internet addiction using machine learning on electroencephalography synchronization and functional connectivity.Psychological medicine · 2025Article
- Detecting depression using an ensemble classifier based on Quality of Life scales.Brain informatics · 2021Article
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Authors and funding
4 authors.
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Abstract
Internet usage has increased dramatically in recent decades. With this growing usage trend, the negative impacts of Internet usage have also increased significantly. One recurring concern involves users with Internet addiction, whose Internet usage has become excessive and disrupted their lives. In order to detect users with Internet addiction and disabuse their inappropriate behavior early, a secure Web service-based EMBAR (ensemble classifier with case-based reasoning) system is proposed in this study. The EMBAR system monitors users in the background and can be used for Internet usage monitoring in the future. Empirical results demonstrate that our proposed ensemble classifier with case-based reasoning (CBR) in the proposed EMBAR system for identifying users with potential Internet addiction offers better performance than other classifiers.
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