I just bought the MEAP Mahout in action book and think it is awesome. It is very helpful to see the simple examples and the plain English.
I am having trouble with one use case in particular... making a recommendation for either an anonymous user or for a user that has never performed any action at all.... (e.g. the first time the user logs in after signing up for an account). Even in the Manning book, the documented workaround is to cluster the users... but even then (in the case of an anonymous user or before the very first interaction) there is no way to cluster a user successfully. In what ways do other people solve this initial discovery issue inside of Mahout? (i.e. outside of using a "stats table" that contains the most popular items and using that to produce results on behalf of the recommender). Thanks, Joe
