RecSys Basics
State-of-the-Art Algorithms
"What are/is the state-of-the-art recommendation algorithm(s)?" is a question that should be a no-brainer to answer for any recommender-system researcher and developer. However, the answer is typical "I don't know, at least not for sure". The recommender-system community faces a reproducibility crisis, which makes it almost impossible to say what algorithms are truly state-of-the-art. In...
Recommender Systems Definition
A recommender system (RecSys) is an information filtering system that suggests relevant items such as products, content, or services to users based on their preferences, behavior, past interactions or general information such as popularity. Recommender systems use algorithms, often but not always based on machine learning, to predict what users might like, without explicit user...
Example Applications
Recommender Systems are used in a variety of applications. The most popular ones being probably movies, news, and e-commerce. However, recommendation systems are used in many applications more. To get an initial idea of what recommender systems are and what they can do, have a look at the following blog posts. Google Android Users May...
History
To fully grasp the concept of recommender systems, a bit of history doesn't harm. On this page, you find our blog posts relating to the history of recommender systems. Against All Odds: Netflix, From Mail-Order DVD Rentals to Streaming Dominance [Shawn Knight @ TechSpot] Shown Knight from Techspot writes about the history of Netflix and...