JOURNAL ARTICLE

Fast PNN-based clustering using k-nearest neighbor graph

Abstract

Search for nearest neighbor is the main source of computation in most clustering algorithms. We propose the use of nearest neighbor graph for reducing the number of candidates. The number of distance calculations per search can be reduced from O(N) to O(k) or where N is the number of clusters, and k is the number of neighbors in the graph. We apply the proposed scheme within agglomerative clustering algorithm known as the PNN algorithm.

Keywords:
Nearest-neighbor chain algorithm Cluster analysis k-nearest neighbors algorithm Computer science Graph Nearest neighbor search Computation Nearest neighbor graph Pattern recognition (psychology) Best bin first Artificial intelligence Correlation clustering Algorithm Canopy clustering algorithm Theoretical computer science

Metrics

18
Cited By
1.54
FWCI (Field Weighted Citation Impact)
10
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Clustering Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence

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