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From prasenjit mukherjee <prasen....@gmail.com>
Subject Re: newbie question: LSA anaylsis + others
Date Wed, 17 Jun 2009 06:07:21 GMT
Well, there is a  PLSI implementation using Pig ( over Hadoop ) as a mahout
patch : https://issues.apache.org/jira/browse/MAHOUT-106

-P

On Wed, Jun 17, 2009 at 7:34 AM, Paul Jones <paul_jonez99@yahoo.co.uk>wrote:

> Hi to one and all
>
> First time on this list, have read through the wiki, faq and other docs,
> but before I dived further into Mahout I had a few questions or should I say
> clarifications.
> I am looking for a system which would allow me to:
>
> 1. Take a set of words
> 2. Build clusters of these words, i.e work out the semantic relationship
> between these (I guess I could use wordnet as a starter) words. i.e
> inter-relationships
> 3. Once clusters have been formed of words, also work out relationship
> between the clusters themselves.
>
> so in essence I could work out that red was similiar to crimson, and hence
> a search on red would produce docs with crimson in them even though red was
> not mentioned.
>
> would mahout work here?
>
> Of course prior to this, there is the problem of cleaning up the data, i.e
> stemming etc.
>
> Now I have read several detailed papers on clustering, ranking, etc, and of
> course some algos are better than others, but to me a platform like Mahout
> seems interesting since you can deploy the existing ones in the system, and
> also later on add others.
>
> Looking at the algorithms it seems as if LSI (PLSI) has not been
> implemented as yet, if so which other algo would "suffice" in this case.
> Admitedley my knowledge of algos is poor to say the least :-). Also where
> would (if it does) Lucene fit in, would it be used to search the results
> after the algo's had been applied ? since it seems as if Lucene just uses a
> weighting system to create the index, or can Mahout do it all.
>
> As you can see confused, but this is my first pass at this system.
>
> tks
>
> Paul
>
> P.S are any of the algo's feedback algo's, i.e so that someone could
> inprove results using user feedback.
>
>
>

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