mahout-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Recommeding on Dynamic Content
Date Tue, 01 Feb 2011 21:14:46 GMT
I don't like their approach.  It doesn't matter what method you use to
optimize the assignment of the co-clusters, they still lack expressive
power.  I also generically don't like non-convex optimizations.

On Tue, Feb 1, 2011 at 11:55 AM, vineet yadav
<vineet.yadav.iiit@gmail.com>wrote:

> Hi Ted,
> Yes, In paper they have mentioned the point that "locally optimized
> co-clustering gives poor result in iterative learning", so they have used
> evolutionary co-clustering that gives better result.
> Thanks
> Vineet Yadav
>
> On Wed, Feb 2, 2011 at 1:12 AM, Ted Dunning <ted.dunning@gmail.com> wrote:
>
> > Co-clustering typically doesn't give really hot results (at least in my
> > reading and experience).
> >
> > On Tue, Feb 1, 2011 at 11:25 AM, vineet yadav
> > <vineet.yadav.iiit@gmail.com>wrote:
> >
> > > Hi Gökhan,
> > > Also check out paper "Incremental Collaborative Filtering via
> > Evolutionary
> > > Co-clustering"(
> > > http://www.dollar.biz.uiowa.edu/~street/research/recsys10_ecoc.pdf<
> http://www.dollar.biz.uiowa.edu/%7Estreet/research/recsys10_ecoc.pdf>),
> > In
> > > paper, author proposed a method to  use new data in  collaborative
> > > filtering
> > > model incrementally. Here co-clustering is used to cluster row and
> > > column(items and user) simultaneously. Also check master thesis
> > > "RECOMMENDING
 ARTICLES FOR AN
 ONLINE NEWSPAPER
"  (
> > > http://www.ilk.uvt.nl/downloads/pub/papers/hait/kneepkens2009.pdf).
> > > Thanks
> > > Vineet Yadav
> > >
> > > On Tue, Feb 1, 2011 at 10:32 PM, Ted Dunning <ted.dunning@gmail.com>
> > > wrote:
> > >
> > > > Sebastian,
> > > >
> > > > Have you read the Elkan paper?  Are you interested in (partially)
> > content
> > > > based recommendation?
> > > >
> > > > On Tue, Feb 1, 2011 at 2:02 AM, Sebastian Schelter <ssc@apache.org>
> > > wrote:
> > > >
> > > > > Hi Gökhan,
> > > > >
> > > > > I wanna point you to some papers I came across that deal with
> similar
> > > > > problems:
> > > > >
> > > > > "Google News Personalization: Scalable Online Collaborative
> > Filtering"
> > > (
> > > > > http://www2007.org/papers/paper570.pdf ), this paper describes how
> > > > Google
> > > > > uses three algorithms (two of which cluster the users) to achieve
> > > online
> > > > > recommendation of news articles.
> > > > >
> > > > > "Feature-based recommendation system" (
> > > > > http://glaros.dtc.umn.edu/gkhome/fetch/papers/fbrsCIKM05.pdf ),
> this
> > > > > approach didn't really convince me and I think the paper is lacking
> a
> > > lot
> > > > of
> > > > > details, but it might still be an interesting read.
> > > > >
> > > > > --sebastian
> > > > >
> > > > > On 01.02.2011 00:26, Gökhan Çapan wrote:
> > > > >
> > > > >> Hi,
> > > > >>
> > > > >> I've made a search, sorry in case this is a double post.
> > > > >> Also, this question may not be directly related to Mahout.
> > > > >>
> > > > >> Within a domain which is enitrely user generated and has a very
> big
> > > item
> > > > >> churn (lots of new items coming, while some others leaving the
> > > system),
> > > > >> what
> > > > >> do you recommend to produce accurate recommendations using Mahout
> > (Not
> > > > >> just
> > > > >> Taste)?
> > > > >>
> > > > >> I mean, as a concrete example, in the eBay domain, not Amazon's.
> > > > >>
> > > > >> Currently I am creating item clusters using LSH with MinHash
(I am
> > not
> > > > >> sure
> > > > >> if it is in Mahout, I can contribute if it is not), and produce
> > > > >> recommendations using these item clusters (profiles). When a
new
> > item
> > > > >> arrives, I find its nearest profile, and recommend the item where
> > its
> > > > >> belonging profile is recommended to. Do you find this approach
> good
> > > > >> enough?
> > > > >>
> > > > >> If you have a theoretical idea, could you please point me to
some
> > > > related
> > > > >> papers?
> > > > >>
> > > > >> (As an MSc student, I can implement this as a Google Summer of
> Code
> > > > >> project,
> > > > >> with your mentoring.)
> > > > >>
> > > > >> Thanks in advance
> > > > >>
> > > > >>
> > > > >
> > > >
> > >
> >
>

Mime
  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message