Recommender system
Information filtering system to predict users' preferences / From Wikipedia, the free encyclopedia
Dear Wikiwand AI, let's keep it short by simply answering these key questions:
Can you list the top facts and stats about Recommendation algorithm?
Summarize this article for a 10 year old
A recommender system, or a recommendation system (sometimes replacing "system" with terms such as "platform", "engine", or "algorithm"), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user.[1][2][3] Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.[1][4]
It has been suggested that Content discovery platform be merged into this article. (Discuss) Proposed since November 2023. |
This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these template messages)
|
Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read.[1] Recommender systems are used in a variety of areas, with commonly recognised examples taking the form of playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders.[5][6] These systems can operate using a single type of input, like music, or multiple inputs within and across platforms like news, books and search queries. There are also popular recommender systems for specific topics like restaurants and online dating. Recommender systems have also been developed to explore research articles and experts,[7] collaborators,[8] and financial services.[9]