Abstract
Recommendation systems are now widely used in many commercial applications. This tutorial focuses on the evaluation of such systems, from an application-oriented view. The tutorial recommends best practices, suggests a protocol for the evaluation process, and reviews a set of metrics that can be evaluated. The practices in this paper are motivated by similar procedures in nearby areas, such as machine learning, and information retrieval.
| Original language | American English |
|---|---|
| Pages (from-to) | 225-236 |
| Number of pages | 12 |
| Journal | AI Communications |
| Volume | 26 |
| Issue number | 2 |
| DOIs | |
| State | Published - 22 Jul 2013 |
Keywords
- Recommender systems
- evaluation
All Science Journal Classification (ASJC) codes
- Artificial Intelligence