Abstract
Performance of a cognitive personal assistant, RADAR, consisting of multiple machine learning components, natural language processing, and optimization was examined with a test explicitly developed to measure the impact of integrated machine learning when used by a human user in a real world setting. Three conditions (conventional tools, Radar without learning, and Radar with learning) were evaluated in a large-scale, between-subjects study. The study revealed that integrated machine learning does produce a positive impact on overall performance. This paper also discusses how specific machine learning components contributed to human-system performance.
Original language | English (US) |
---|---|
Pages | 182-188 |
Number of pages | 7 |
State | Published - Dec 1 2007 |
Event | 2007 Performance Metrics for Intelligent Systems Workshop, PerMIS'07 - Gaithersburg, MD, United States Duration: Aug 28 2007 → Aug 30 2007 |
Other
Other | 2007 Performance Metrics for Intelligent Systems Workshop, PerMIS'07 |
---|---|
Country | United States |
City | Gaithersburg, MD |
Period | 8/28/07 → 8/30/07 |
Keywords
- Evaluation
- Intelligent systems
- Machine learning
- Mixed-initiative assistants
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Control and Systems Engineering