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2005
Springer

Local Clustering of Large Graphs by Approximate Fiedler Vectors

9 years 1 months ago
Local Clustering of Large Graphs by Approximate Fiedler Vectors
Vectors [Extended Abstract] Pekka Orponen and Satu Elisa Schaeffer Laboratory for Theoretical Computer Science, P.O. Box 5400 FI-02015 TKK Helsinki University of Technology, Finland We address the problem of determining the natural neighbourhood of a given node i in a large nonunifom network G in a way that uses only local computations, i.e. without recourse to the full adjacency matrix of G. We view the problem as that of computing potential values in a diffusive system where node i is fixed at zero potential, and the potentials at the other nodes are then induced by the adjacency relation of G. This point of view leads to a constrained spectral clustering approach. We observe that a gradient method for computing the respective Fiedler vector values at each node can be implemented in a local manner, leading to our eventual algorithm. The algorithm is evaluated experimentally using two types of nonuniform networks: randomised “caveman graphs” and a scientific collaboration networ...
Pekka Orponen, Satu Elisa Schaeffer
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where WEA
Authors Pekka Orponen, Satu Elisa Schaeffer
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