If you are interested in a particular sub-field of recommender systems, a literature survey about that sub-field likely is the best place to start. The following table provides you with an overview of some surveys. If you feel an important survey is missing, let us know. If an important survey does not exist… write one yourself! :-).
Finding recommender-system datasets is a challenge. The survey by Chapman et al. may help by providing a thorough overview of dataset search engines for all kinds of datasets, not only relating to recommender systems. Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to […]
Recommender systems are software applications that help users to find items of interest in situations of information overload. Current research often assumes a one-shot interaction paradigm, where the users’ preferences are estimated based on past observed behavior and where the presentation of a ranked list of suggestions is the main, one-directional form of user interaction. […]
Collaborative filtering recommendation systems provide recommendations to users based on their own past preferences, as well as those of other users who share similar interests. The use of recommendation systems has grown widely in recent years, helping people choose which movies to watch, books to read, and items to buy. However, users are often concerned […]