%0 Journal Article %A Tkalcic, Marko %A Košir, Andrej %A Tasič, Jurij %A Odić, Ante %D 2012 %T LDOS CAMRA 2011 submission %U https://figshare.com/articles/journal_contribution/LDOS_CAMRA_2011_submission/94140 %R 10.6084/m9.figshare.94140.v1 %2 https://ndownloader.figshare.com/files/96314 %K context-aware recommender systems %K Computer Engineering %K Applied Computer Science %X

This paper is a report on the work done by the LDOS
team (from the University of Ljubljana Faculty of electri-
cal engineering) on the 2011 RecSys CAMRA (Challenge on
Context-aware Movie Recommendation). We present three
approaches in the track 1 competition which requires to se-
lect the top N recommended items for each household. Our
general approach uses a matrix factorization algorithm to
compute per-user rating predictions. The context is taken
into account using an averaged and weighted sum to cal-
culate the household-based rating predictions. We also ex-
plored how the limiting of true positive candidates with ad-
ditional knowledge from the dataset influences the perfor-
mance of our models.

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