Network Community Detection Based on Co-Neighbor Modularity Matrix with Spectral Clustering

Ji Liu; Lei Li

doi:10.4028/www.scientific.net/AMM.55-57.1237

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 55-57Network Community Detection Based on Co-Neighbor...

Network Community Detection Based on Co-Neighbor Modularity Matrix with Spectral Clustering

Abstract:

The problem of community detection is one of the outstanding issues in the study of network systems. This paper presents co-neighbor modularity matrix to measure the quality of community detection. The problem of community detection is projected into clustering of eigenvectors in Euclidean space. Network community structure is detected with spectral clustering algorithm which is free from the noise of initial mean point in K-mean algorithm. The experimental results suggest that the method is efficient in finding the structure of community.

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Periodical:

Applied Mechanics and Materials (Volumes 55-57)

Pages:

1237-1241

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.55-57.1237

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Online since:

May 2011

Authors:

Ji Liu, Lei Li

Keywords:

Clustering, Community Detection, Modularity, Social Network, Spectral Analysis

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