Fast sparse representative tree splitting via local density for large-scale clustering
Abstract Large-scale clustering remains an active yet challenging task in data mining and machine learning, where existing algorithms often struggle to balance efficiency, accuracy, and adaptability. This paper proposes a novel large-scale clustering framework with three key innovations: (1) Paramet...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-13848-w |
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