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From Sean Owen <sro...@gmail.com>
Subject Re: Recommending items with temporal restrictions
Date Sat, 20 Aug 2011 06:31:49 GMT
The non-distributed code handles this case with Rescorers. There is no
equivalent in the distributed implementation.

However it's fairly easy to hack this into the code. You just need to
modify the final stage where recommendations are computed to reject
items that are not new enough. They will have been used for similarity
calculations already, but then you can filter them out of
recommendations here.

Sean

On Fri, Aug 19, 2011 at 8:39 PM, Bala Rajagopal <bala.rj@hotmail.com> wrote:
>
> Hi,
> My team is working on building a recommendation system to recommend items for the following
use cases:1. Based on User similarity (using org.apache.mahout.cf.taste.hadoop.item.RecommenderJob
as the Base)2. Based on item similarity
> The part where it gets tricky is that we have a temporal restriction on our items (they
are valid only for x days). So in the ideal case, the recommender should/can use the rating
information on all our historical items, but will never recommend any items that are not temporally
available. Based on the historical rating information, we need the list of best matches from
the temporally available items.
> Apart from ideas that involve any pre/post processing activities to filter temporally
invalid item recommendations, we were reaching out to find if somebody out here has ever dealt
with a similar requirement and has found an easier solution to deal with this edge case.
> Any piece of advice, word of caution or streak of brilliance is more than welcome.
> Thanks in advance.
> Bala

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