RECOMMENDATION SYSTEMS (AMBA/Cornell Tech) - 0.25 credits

Recommender systems personalize websites by suggesting content, products, and people most relevant to a current
user. In this session, we'll give a broad overview of recommender systems including common ways to represent users'
interests and generate recommendations, important considerations for recommendation interfaces, and the effects
recommendations can have on people's experiences and consumption patterns.

Professor Cosley is an Associate Professor in Information Science at Cornell; his background is recommender systems
and social computing via a computer science PhD at Minnesota in the GroupLens research group, a pioneering group in
the development of recommender systems. Professor Cosley works on systems that re-purpose people’s behavior in
social media to support reminiscing, reflection, and self-knowledge, as well as systems that modeling and support social
goods in systems including Wikipedia.