So I must use the UserSimilarity objects and the UserBasedRecommender
although I would prefer the ItemBasedRecommender.

OK so use CachingUserSimilarity then. There are versions for both.
Hello,

today I rewrite the code of my recommender-system and use the CachingUserSimilarity and a UserBasedRecommender.

Of course the memory consumption is no longer significantly and there are no more 8 GB in Ram. Otherwise the speed of the recommender-system naturally slows down a little bit. But the first goal is achieved and with that memory usage the system could run at an application server. Later I have to think about the speed and why it is so slow - but first there is another problem:

The UserBasedRecommender don't work for me! In comparative with the Itembased-Recommender the Recommendations of the Userbase-Recommender are really bad. Only/mostly popular Items will be recommended. I think this is because I had a lot of Items and a lot of Users - but the most Users occupied only a few Items and the overlap of Users is sparse. Now there are a few other Users which occupied a lot of Items and randomly own a Item of the User the recommendation is made for - so Items were be recommended that have nothing in common with the profile of the user.

So I have to use a recommender which bases only on the Item-Item-Matrix and the Userprofile from the User the Recommendation is made for: The ItemBasedRecommender. But I compute my Item-Item-Matrix with a UserSimilarity. Is there a way to get a UserSimilarity in a Item-Based-Recommender? Cast it somehow - so that I could compute the Item-Item-Similarity "on the fly" like I do this now?

Otherwise I would precompute the whole Item-Item-Matrix like I do it before and put the Data with Sean's brand new MySQLJDBCItemSimilarity in the ItemBased - System. (I will test this now). Thank you for that!

Regards Thomas

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Thomas Rewig, MusicFinder Developer Team

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