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.Prerequisite:
- C or higher in CS 3358: Data Structures
- -OR-
- Consent of Instructor
Course Objectives:
- Describe different approaches to recommendation
- Infer the recommendation technologies likely used in an application
- Build a basic recommender algorithm
- Interpret evaluation results to select and optimize a recommender algorithm
- Design a recommender-based application (select data sources and types, likely-appropriate algorithms, recommendation presentation style, etc.)
- Recognize and list various and competing concerns in recommender development (business, legal, privacy, security, user interest)
- 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
Offered: