Hello, So, I have begun working with the SVDRecommender implementation. Obviously, a matrix factorization technique will not play nice when we try to add an anon/new user (say via the PAUDM) because we have not re-factorized.
So my question is more from the linear algebra standpoint: is it possible to estimate the new singular vector when adding a small amount of information (i.e. a new user or a new item) to the matrix? Are there assumptions that can be made to simplify this estimate? For instance, could we assume that the addition of a single row or column will have negligible effect on the already computed singular vectors? If this is possible, I would be interested in playing around with the implementation. Can you point me in the right direction? I'll do some more research over the next few days as well. Finally, I have a question about the sequential factorizations in Mahout. Once I have my original matrix factorized, what is the easiest way to serialize the results of the factorization for reading back in at a later time? Would I loop through all the items and users and dump the features for each? How to read that back in then? Thanks for all the help, Much appreciated, Chris
