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A Multi-Relational Hierarchical Clustering Algorithm Based on Shared Nearest Neighbor Similarity

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3 Author(s)

The clustering about relational databases is an active study subject in data mining. In this paper, we introduce a multi-relational hierarchical clustering algorithm based on shared nearest neighbor similarity (MHSNNS). First, this algorithm joins every table through the tuple 1D propagation. Then, groups objects into a large number of relatively small sub-clusters using the shared nearest neighbor algorithm and the cluster cohesion. Last, find the genuine clusters by repeatedly combining these sub-clusters using the cluster separation. The experiment shows the efficiency and scalability of this approach.

Published in:

Machine Learning and Cybernetics, 2007 International Conference on  (Volume:7 )

Date of Conference:

19-22 Aug. 2007