Why do you say that eigenvectors are infeasible? Also, I think your link should have been http://www.cs.utexas.edu/~ddn/papers/sui10.pdf
You accidentally glued some extra text to it. On Sat, Oct 22, 2011 at 10:16 PM, Bae, Jae Hyeon <[email protected]> wrote: > 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 >
