preference for an item or list of items • Use cases: ◦ Product recommendations on Amazon ◦ Music recommendations on Spotify ◦ Book recommendations on Goodreads ◦ Job recommendations on Jobberman? ◦ Hotel recommendations on Hotels.ng? ◦ Friend recommendations on Facebook
of all users • Let V be the set of all items • R is a U by V matrix Goal: Predict the value of the empty cells. Super Story Jennifer’s Diaries Papa Ajasco Saworoide Gibran ? 1 ? ? Adichie ? ? 1 ? Fajuyi 1 ? 1 ?
whose dot product will give you R • Matrix X and Y will have dimension I which is specified by the user or determined via cross validation • I represents the number of latent factors in the each matrix Matrix Factorization (MF)
likes item i P ui - binary value indicating if user u has interacted with item i X u - latent vectors for user u Y i - latent vectors for item i - regularization parameter