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A differential privacy protecting K-means clustering algorithm based on contour coefficients
This paper, based on differential privacy protecting K-means clustering algorithm, realizes privacy protection by adding data-disturbing Laplace noise to cluster center point. In order to solve the problem of Laplace noise randomness which causes the center point to deviate, especially when poor ava...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248925/ https://www.ncbi.nlm.nih.gov/pubmed/30462662 http://dx.doi.org/10.1371/journal.pone.0206832 |