Skip to content

LI-Ke/Recommender-Systems

Repository files navigation

Recommender-Systems

Recommender systems have become extremely common in recent years, and are utilized in a variety of areas: some popular applications include movies, music, news, books, research articles, search queries, social tags, and products in general. There are also recommender systems for experts, collaborators, jokes, restaurants, garments, financial services, life insurance, romantic partners (online dating), and Twitter pages.

Here I will introduce some important algorithms such that Collaborative Filtering and something about Social Recommendation, Collective Inference, Diffusion and Bandits Problems.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages