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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Help for graph processing implementation
Date Sun, 23 Oct 2011 07:30:05 GMT
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 <metacret@gmail.com> 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
>

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