Name
Title | ||
|---|---|---|
A Dynamic Bayesian Network Approach to Location Prediction in Ubiquitous Computing Environments. |
Abstract | ||
|---|---|---|
The ability to predict the future contexts of users significantly improves service quality and user satisfaction in ubiquitous computing environments. Location prediction is particularly useful because ubiquitous computing environments can dynamically adapt their behaviors according to a user's future location. In this paper, we present an inductive approach to recognizing a user's location by establishing a dynamic Bayesian network model. The dynamic Bayesian network model has been evaluated with a set of contextual data collected from undergraduate students. The evaluation result suggests that a dynamic Bayesian network model offers significant predictive power. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-16699-0_9 | ADVANCES IN INFORMATION TECHNOLOGY |
Keywords | Field | DocType |
Dynamic Bayesian Networks,Context Prediction,Ubiquitous Computing | Data mining,Service quality,Predictive power,Computer science,Contextual design,Ubiquitous computing,Location prediction,Dynamic Bayesian network | Conference |
Volume | ISSN | Citations |
114 | 1865-0929 | 5 |
PageRank | References | Authors |
0.46 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sunyoung Lee | 1 | 5 | 0.80 |
| Kun Chang Lee | 2 | 994 | 94.73 |
| Heeryon Cho | 3 | 70 | 9.38 |