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From: Saikat Kanjilal <sxk1969@hotmail.com>
To: "solr-user@lucene.apache.org" <solr-user@lucene.apache.org>,
	"java-user@lucene.apache.org" <java-user@lucene.apache.org>
Subject: RE: Content based recommender using lucene/solr
Date: Fri, 28 Jun 2013 10:42:32 -0700
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Why not just use mahout to do this=2C there is an item similarity algorithm=
 in mahout that does exactly this :)

https://builds.apache.org/job/Mahout-Quality/javadoc/org/apache/mahout/cf/t=
aste/hadoop/similarity/item/ItemSimilarityJob.html

You can use mahout in distributed and non-distributed mode as well.

> From: lcguerrerocovo@gmail.com
> Date: Fri=2C 28 Jun 2013 12:16:57 -0500
> Subject: Content based recommender using lucene/solr
> To: solr-user@lucene.apache.org=3B java-user@lucene.apache.org
>=20
> Hi=2C
>=20
> I'm using lucene and solr right now in a production environment with an
> index of about a million docs. I'm working on a recommender that basicall=
y
> would list the n most similar items to the user based on the current item
> he is viewing.
>=20
> I've been thinking of using solr/lucene since I already have all docs
> available and I want a quick version that can be deployed while we work o=
n
> a more robust recommender. How about overriding the default similarity so
> that it scores documents based on the euclidean distance of normalized it=
em
> attributes and then using a morelikethis component to pass in the
> attributes of the item for which I want to generate recommendations? I kn=
ow
> it has its issues like recomputing scores/normalization/weight applicatio=
n
> at query time which could make this idea unfeasible/impractical. I'm at a
> very preliminary stage right now with this and would love some suggestion=
s
> from experienced users.
>=20
> thank you=2C
>=20
> Luis Guerrero
 		 	   		  =

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