Hi, Have a look at http://www.youtube.com/watch?v=13yQbaW2V4Y . I'd say it's easier than Mahout, especially if you already have and know your way around Solr.
Otis -- Solr & ElasticSearch Support -- http://sematext.com/ Performance Monitoring -- http://sematext.com/spm On Fri, Jun 28, 2013 at 2:02 PM, Luis Carlos Guerrero Covo <lcguerreroc...@gmail.com> wrote: > Hey saikat, thanks for your suggestion. I've looked into mahout and other > alternatives for computing k nearest neighbors. I would have to run a job > and computer the k nearest neighbors and track them in the index for > retrieval. I wanted to see if this was something I could do with lucene > using lucene's scoring function and solr's morelikethis component. The job > you specifically mention is for Item based recommendation which would > require me to track the different items users have viewed. I'm looking for > a content based approach where I would use a distance measure to establish > how near items are (how similar) and have some kind of training phase to > adjust weights. > > > On Fri, Jun 28, 2013 at 12:42 PM, Saikat Kanjilal <sxk1...@hotmail.com>wrote: > >> Why not just use mahout to do this, there is an item similarity algorithm >> in mahout that does exactly this :) >> >> >> https://builds.apache.org/job/Mahout-Quality/javadoc/org/apache/mahout/cf/taste/hadoop/similarity/item/ItemSimilarityJob.html >> >> You can use mahout in distributed and non-distributed mode as well. >> >> > From: lcguerreroc...@gmail.com >> > Date: Fri, 28 Jun 2013 12:16:57 -0500 >> > Subject: Content based recommender using lucene/solr >> > To: solr-user@lucene.apache.org; java-u...@lucene.apache.org >> > >> > Hi, >> > >> > 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 >> basically >> > would list the n most similar items to the user based on the current item >> > he is viewing. >> > >> > 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 >> on >> > a more robust recommender. How about overriding the default similarity so >> > that it scores documents based on the euclidean distance of normalized >> item >> > attributes and then using a morelikethis component to pass in the >> > attributes of the item for which I want to generate recommendations? I >> know >> > it has its issues like recomputing scores/normalization/weight >> application >> > 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 >> suggestions >> > from experienced users. >> > >> > thank you, >> > >> > Luis Guerrero >> >> > > > > -- > Luis Carlos Guerrero Covo > M.S. Computer Engineering > (57) 3183542047
