Editing Recommender system (section)

=== Risk-aware recommender systems ===
The majority of existing approaches to recommender systems focus on recommending the most relevant content to users using contextual information, yet do not take into account the risk of disturbing the user with unwanted notifications. It is important to consider the risk of upsetting the user by pushing recommendations in certain circumstances, for instance, during a professional meeting, early morning, or late at night. Therefore, the performance of the recommender system depends in part on the degree to which it has incorporated the risk into the recommendation process. One option to manage this issue is ''DRARS'', a system which models the context-aware recommendation as a [[Multi-armed bandit|bandit problem]]. This system combines a content-based technique and a contextual bandit algorithm.<ref name="Bouneffouf2013">{{cite thesis | type=Ph.D. thesis | last = Bouneffouf  | first = Djallel | title= DRARS, A Dynamic Risk-Aware Recommender System | publisher = Institut National des Télécommunications | year = 2013 | url = http://tel.archives-ouvertes.fr/tel-01026136/fr/}}</ref>