Peng Cheng created MAHOUT-1274:
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             Summary: SGD-based Online SVD recommender
                 Key: MAHOUT-1274
                 URL: https://issues.apache.org/jira/browse/MAHOUT-1274
             Project: Mahout
          Issue Type: New Feature
          Components: Collaborative Filtering
            Reporter: Peng Cheng
            Assignee: Sean Owen


an online SVD recommender is otherwise similar to an offline SVD recommender 
except that, upon receiving one or several new recommendations, it can add them 
into the training dataModel and update the result accordingly in real time.

an online SVD recommender should override setPreference(...) and 
removePreference(...) in AbstractRecommender such that the factorization result 
is updated in O(1) time and without retraining.

Right now the slopeOneRecommender is the only component possessing such 
capability.

Since SGD is intrinsically an online algorithm and its CF implementation is 
available in core-0.8 (See MAHOUT-1089, MAHOUT-1272), I presume it would be a 
good time to convert it. Such feature could come in handy for some websites.

Implementation: Adding new users, items, or increasing rating matrix rank are 
just increasing size of user and item matrices. Reducing rating matrix rank 
involves just one svd. The real challenge here is that sgd is NO ONE-PASS 
algorithm, multiple passes are required to achieve an acceptable optimality and 
even more so if hyperparameters are bad. But here are two possible circumvents:

1. Use one-pass algorithms like averaged-SGD, not sure if it can ever work as 
applying stochastic convex-opt algorithm to non-convex problem is anarchy. But 
it may be a long shot.

2. Run incomplete passes in each online update using ratings randomly sampled 
(but not uniformly sampled) from latest dataModel. I don't know how exactly 
this should be done but new rating should be sampled more frequently. Uniform 
sampling will results in old ratings being used more than new ratings in total. 
If somebody has worked on this batch-to-online conversion before and share his 
insight that would be awesome. This seems to be the most viable option, if I 
get the non-uniform pseudorandom generator that maintains a cumulative uniform 
distribution I want.

I found a very old ticket (MAHOUT-572) mentioning online SVD recommender but it 
didn't pay off. Hopefully its not a bad idea to submit a new tickets.

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