Name
Abstract | ||
|---|---|---|
Smart environments are able to support users during their daily life. For example, smart energy systems can be used to support energy saving by controlling devices, such as lights or displays, depending on context information, such as the brightness in a room or the presence of users. However, proactive decisions should also match the users’ preferences to maintain the users’ trust in the system. Wrong decisions could negatively influence the users’ acceptance of a system and at worst could make them abandon the system. In this paper, a trust-based model, called User Trust Model (UTM), for automatic decision-making is proposed, which is based on Bayesian networks. The UTM’s construction, the initialization with empirical data gathered in an online survey, and its integration in an office setting are described. Furthermore, the results of a live study and a live survey analyzing the users’ experience and acceptance are presented. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s11257-015-9160-8 | User Modeling and User-Adapted Interaction |
Keywords | Field | DocType |
Computational trust,Context awareness,Proactive systems,Energy saving | World Wide Web,Smart environment,Computer science,Context awareness,Bayesian network,Human–computer interaction,Artificial intelligence,Computational trust,Initialization,Machine learning | Journal |
Volume | Issue | ISSN |
25 | 3 | 0924-1868 |
Citations | PageRank | References |
9 | 0.47 | 34 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephan Hammer | 1 | 29 | 3.18 |
| Michael Wißner | 2 | 9 | 0.47 |
| Elisabeth André | 3 | 3634 | 433.65 |