Similarity Metric Based on Resistance Distance and its Applications to Data Clustering

Geng Qi Guo; Wen Jun Xiao; Bin Lu

doi:10.4028/www.scientific.net/AMM.556-562.3654

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Similarity Metric Based on Resistance Distance and...

Similarity Metric Based on Resistance Distance and its Applications to Data Clustering

Abstract:

We propose a new clustering method that uses a similarlity metric deived from electrical resistance networks. The proposed metric allows us to quantify the mutual relevancy between data objects or nodes. We show how to derive the metric from the data collection and how to apply it to various application contexts. Our theoretical analyses and experiments show the excellent potential of the method to identifying clusters of networks and to improving data clustering performance on a number of data sets.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3654-3657

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3654

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Online since:

May 2014

Authors:

Geng Qi Guo*, Wen Jun Xiao, Bin Lu

Keywords:

Clustering, High-Performance Comparison, Network Similairty, Resistance Distance, Similarity Metric

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* - Corresponding Author

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