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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...
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| Veröffentlicht in: | PLoS One |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2018
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6248925/ https://ncbi.nlm.nih.gov/pubmed/30462662 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0206832 |
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