Hi I am implementing graph clustering algorithm based on hadoop and mahout. This is my term project of data mining course.
Spectral method of graph clustering needs calculation of eigenvectors, which is not practically efficient with the large scale graph. Thus, there exists multi-level graph clustering method without eigenvectors. This contains graph coarsening, base clustering, refining. Refining stage can be done with weighted kernel k-means clustering which is not so difficult to be implemented in MapReduce way, but the problem is graph coarsening. Pseudocode is on this paper http://www.cs.utexas.edu/~ddn/papers/sui10.pdfLike any graph processing algorithm, this algorithm does not look easy to be intuitively implemented in MapReduce way. So, I need a help from experts more proficient at converting single thread graph algorithm to MapReduce way. If this work is done smoothly, I will contribute this graph clustering algorithm to Mahout if I am allowed to do so. Thank you! Best, Jae
