CS 4379Q - Introduction to Recommender Systems

Course Description:

This course covers the basic concepts of recommender systems, including personalization algorithms, evaluation tools, and user experiences. We will discuss how recommender systems are deployed in e-commerce sites, social networks, and many other online systems. Additionally, we will review current research in the field.


  • Consent of Instructor

Course Objectives:

  1. Describe different approaches to recommendation

  2. Infer the recommendation technologies likely used in an application

  3. Build a basic recommender algorithm

  4. Interpret evaluation results to select and optimize a recommender algorithm

  5. Design a recommender-based application (select data sources and types, likely-appropriate algorithms, recommendation presentation style, etc.)

  6. Recognize and list various and competing concerns in recommender development (business, legal, privacy, security, user interest)

  7. Identify and explain user's goals and needs for a recommender application

Course Notes:

New course effective Spring 2015

Section Info:

Lecture/Lab Hours: 3 hours lecture