Computer Science 691RS - S-Intro to Recommender Systems

Recommender Systems (RS) are key technical components in many online applications, such as product recommendation, video recommendation, or stream recommendation in social networks. In this course, we cover the applications and technical details of recommender systems, including: 1) Historical overview 2) Major recommendation frameworks, including content-based, collaborative filtering, and hybrid recommender systems; 3) Current techniques for recommendation, including matrix factorization, frequent pattern mining, sentiment analysis, deep learning, and economic models; 4) Analysis of recommendation applications. From this course, students will develop an understanding of the research issues, technical basis, and practical applications of personalized recommender systems.

Open to Graduate Computer Science students only. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.