Abstract
In the contemporary era of the internet, safeguarding children's rights emerges as a critical concern necessitating immediate attention. Given children's heightened vulnerability within society, the legal framework must prioritize their protection, reinforcing their agency and safeguarding their rights through legislative measures. This study proposes an innovative differential clustering algorithm specifically designed to uphold children's rights. Through rigorous experimentation, the algorithm achieves an Adjusted Rand Index (ARI) approaching 2, showcasing its effectiveness in offering targeted differential protection for children's rights while maintaining high clustering precision. The paper emphasizes the importance of noise reduction through iterative central point optimization to stabilize cluster configurations, with the fusion of multiple clusters serving to mitigate noise impacts on data points and yield robust clustering outcomes. Consequently, this research delivers reliable clustering results while preserving the confidentiality of children's rights information.
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