IS 4450 User Modeling and Recommender Systems 3.0 Credits
An application-oriented course on recommending information, products, and other items, along with predictive modeling of user and customer behavior and/or preference to support recommendation and other forms of personalized information and commerce systems. Introduces fundamental and practical aspects of recommendation and personalization, including data, user, and content models; core recommendation approaches (collaborative filtering, and content- and knowledge-based methods); evaluating recommender systems and personalized information access; user characteristics and interaction; and social impact of recommendation and personalization. Lectures and assignments include examples spanning applications and recommendation domains, including both information-oriented systems and e-commerce.
Repeat Status: Not repeatable for credit
Prerequisites: IS 3330 [Min Grade: D] or CS 3520 [Min Grade: D] or INFO 213 [Min Grade: D] or CS 383 [Min Grade: D]