Recommender Systems (RSs) play an increasingly important role in video-on-demand web applications -- such as YouTube and Netix -- characterized by a very large catalogs of videos and movies. Their goal is to filter information and to recommend to users only the videos that are likely of interest to them. Recommendations are traditionally generated on the basis of user's preferences on movies' attributes, such as genre, director, actors. Preferences on attributes are implicitly detected by analyzing the user's past opinions on movies.
No takes yet. Share an insight, caveat, or question.
Deldjoo et al. (2015) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: