Short Course: Recommendation Tools, Spring 2016

Instructor: Dr. Michael Hahsler


Course Description

This course will introduce recommender system techniques and focus on the R package recommenderlab. We will cover non-personalized, content-based and collaborative methods for producing recommendations. The students will learn how to prepare data, how to perform experiments using different recommendation strategies, and how to evaluate the recommendation quality.

Prerequisites: Basic R skills.


Day 1: Introduction

Day 2: Tools

Day 3: Recommendation methods

Day 4: Evaluation and other topics

Reading List and Textbook

Mandatory pre-class reading list

  1. Paul Resnick and Hal R. Varian. 1997. Recommender systems. Commun. ACM 40, 3 (March 1997), 56-58. Link
  2. Francesco Ricci, Lior Rokach and Bracha Shapira. 2010. Introduction to Recommender Systems Handbook. Link

More reading

Text book (optional)


Software and Data Used in Class

Example Recommender Systems

Learning resources

Michael Hahsler
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