Survey: Affective Recommender Systems Techniques

Abstract

Recommender systems (RSs) are software tools or techniques that support the user in the decision-making process by suggesting possibilities that the system predicts. RSs are associated with numerous applications such as Amazon.com, for a book recommendation, compact disks, and other items, MovieLens, for the movie, and VERIFIED technologies, for news articles recommendation. There's a critical range as of late showed up which is an affective recommender framework. The affective recommender is related to human behaviors. Due to this combination and distinctive interests, more statement is required, since it is in awkward organize and creating as compared to other ranges. So we have done a literature survey within affective recommender systems techniques. In affective recommender field, we tried to illustrate how the affective behavior of the user can be used in recommender systems.