Divide-and-Conquer Algorithm for Creating Neighborhood Graph for Clustering

Authors:
Olli Virmajoki;Pasi Franti
Affiliations:
University of Joensuu, Finland;University of Joensuu, Finland
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Year:
2004

Citing 0
Cited 2

Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection

The Journal of Machine Learning Research

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Abstract

K-nearest neighbor graph has been used for reducing the number of distance calculations in PNN-based clustering. The bottleneck of the approach is the creation of the graph. In this paper, we develop a fast divide-and-conquer method for graph creation based on algorithm previously used in the closest pair problem. The proposed algorithm is then applied to agglomerative clustering, in which it outperforms previous projection-based algorithm for high dimensional spatial data sets.