Was thinking about filtering out all but the top x% of items to get things the user is likely to have heard about if not seen. Do this before any factorizing or clustering.
Yes, that's why I'm not convinced it will be useful but an interesting experiment now that we have the online Solr recommender. Soon we'll have category and description metadata from the crawler. We can experiment with things like category boosting if a category trend emerges during the browsing session and I suspect it often does--maybe release date etc. The ease of mixing metadata with behavior is another thing worth experimenting with.