Two-way latent grouping model for user preference prediction
Eerika Savia, Kai Puolamäki, Janne Sinkkonen and Samuel Kaski
In: UAI 2005, 26-29 July 2005, Edinburgh, Scotland.
We introduce a novel latent grouping model for predicting the
relevance of a new document to a user. The model assumes
a latent group structure for both users and documents. We compared
the model against a state-of-the-art method, the User Rating
Profile model, where only users have a latent group structure.
We estimate both models by Gibbs sampling. The
new method predicts relevance more accurately for new documents
that have few known ratings. The reason is that
generalization over documents then becomes necessary and hence the
two-way grouping is profitable.