Recommender systems are widely studied, and there are many approaches used, but there are two that are probably most prevalent: content-based filtering and collaborative filtering. Recently, other approaches, such as ranking models, have also gained in popularity. In practice, many approaches are hybrids, incorporating elements of many different methods into a model or combination of models.
Types of recommendation models
Content-based filtering
Content-based methods try to use the content or attributes of an item, together with some notion of similarity between two pieces of content, to generate items similar to a given item. These attributes are often textual content, such as titles, names, tags, and other metadata attached to an item, or in the case of media,...