Collaborative filtering (CF) is a process to filter information or patterns with collaboration among multiple agents and resources. The main idea of CF is to effectively extract useful information from the overwhelming amount of collected data. This article discusses the perception of CF techniques and explains how to utilize CF in a recommender system (RS). RS provides recommendations to an active user based on items that other similar users prefer. CF makes automatic predictions of a user’s interests by utilizing stored data of various users, which makes it a key method for RS.
- Aggarwal, C. C. (2016). An introduction to recommender systems. In Recommender systems (pp. 1–28). Cham: Springer.Google Scholar