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From "Sean Owen (JIRA)" <>
Subject [jira] Commented: (MAHOUT-418) Computing the pairwise similarities of the rows of a matrix
Date Mon, 21 Jun 2010 17:23:26 GMT


Sean Owen commented on MAHOUT-418:

Let's see how far apart these two implementations are. It would be great to spend some time
unifying them a bit, now, if there is no hurry to get a second implementation in.

Yes, the recommender-specific job needs an additional phase at the start and end, to map from
longs to ints and back. It does do this. This can remain. But once data is converted into
vectors, the general code you are creating should be able to take over?

Both implementations can write the whole matrix, and take the same approach to self-similarity.
That is I think you are welcome to make them both assume the same thing. Just compute and
store everything for good measure.

If those are the only differences, it really seems like they are doing the same thing and
this can be a move of code rather than copy. I think you should feel free to go this way,
even if it requires change in other code. I can help adjust other code if it means some assumptions
have changed.

That way you are not burdened with maintaining two implementations. I think that makes MAHOUT-420

What do you think, are you keen to commit this, or open to pushing towards one implementation?

> Computing the pairwise similarities of the rows of a matrix
> -----------------------------------------------------------
>                 Key: MAHOUT-418
>                 URL:
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Math
>            Reporter: Sebastian Schelter
>         Attachments: MAHOUT-418-2.patch, MAHOUT-418.patch
> In response to the wish from MAHOUT-362 and the latest discussion on the mailing list
started by Kris Jack about computing a document similarity matrix, I tried to generalize the
approach we're already using to compute the item-item-similarities for collaborative filtering.
> The job in the patch computes the pairwise similarity of the rows of a matrix in a distributed
manner, is uses a SequenceFile<IntWritable,VectorWritable> as input and outputs such
a file too. Custom similarity implementations can be supplied, I've already implemented tanimoto
and cosine for demo and testing purposes. The algorithm is based on the one presented here:
> I'd be glad if someone could verify the applicability of this approach by running it
with a reasonably large input, I'm also worried that it might buffer to much data in certain
> If you decide to include it in mahout, some more efforts and decisions (like more tests,
more similarity measures, integration with DistributedRowMatrix) would need to be made, I

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