Full implementation is complex: it needs advanced linear algebra.
Types of Recommender Systems:
- Content based. Focus on the attributes of the items: the usual “related items”.
- Collaborative filter (CF). Uses “wisdom of the crowd” to recommend items: eg Amazon. CF is most used on content based systems. It can do feature learning by itself.
The Movie land dataset of movies to study. These methods can be:
– Memory based CF: singular value decomposition.
– Collaborative CF: computing cosine similarity.