What Is Collaborative Filtering?

Collaborative filtering is simply to use the preferences of a group of people with similar interests and common experience to recommend information that users are interested in. Individuals give a considerable response to the information (such as ratings) through a cooperative mechanism and record it to achieve the purpose of filtering To help others filter information, responses are not necessarily limited to those of particular interest, and records of particularly uninteresting information are also important.

Here are a few important things in the history of "collaborative filtering"

E-commerce

User-based collaborative filtering

Use similar statistics to get neighbors with similar hobbies or interests

Item-based recommendation algorithm can solve some problems of User-based collaborative filtering, but there are still many problems to be solved. The most typical ones are Sparsity and Cold-start. The effect is better during cold boot. difference. There are also issues such as new user problems and algorithm robustness. Collaborative filtering has considerable applications as a typical recommendation technology, and many technologies are being researched around collaborative filtering. In the era of more and more types of information and expressions, where the old-style information classification filtering system cannot meet, it is expected that collaborative filtering methods can be used to solve it in the future ^[3] .