A spectral algorithm for topographical Co-clustering
Nicoleta Rogovschi, Lazhar Labiod, Mohamed Nadif · 2012
This paper proposes a spectral algorithm for cross-topographic clustering. It leads to a simultaneous clustering on the rows and columns of data matrix, as well as the projection of the clusters on a two-dimensional grid while preserving the topological order of the initial data. The proposed algorithm is based on a spectral decomposition of this data matrix and the definition of a new matrix taking into account the co-clustering problem. The proposed approach has been validated on multiple datasets and the experimental results have shown very promising performance.