Name
Abstract | ||
|---|---|---|
Identifying users frequent behaviors is considered as a key step to achieve real intelligent environments that support people in their daily lives. These patterns can be used in many different applications. An algorithm that compares current behaviors of the users with previously discovered frequent behaviors and detects shifts has been developed. In addition, it identifies the differences between both behaviors. Identified shifts can be used not only to adapt frequent behaviors, but also to detect initial signs of some disease linked to behavioral modifications, such as depression, Alzheimer's. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-35395-6_12 | IWAAL |
Keywords | Field | DocType |
user behavior shift detection,identified shift,detects shift,identifying user,different application,key step,initial sign,intelligent environment,daily life,current behavior,behavioral modification,frequent behavior,shift detection | Computer science,Step detection,Human–computer interaction | Conference |
Citations | PageRank | References |
3 | 0.40 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asier Aztiria | 1 | 181 | 13.88 |
| Golnaz Farhadi | 2 | 363 | 23.61 |
| Hamid Aghajan | 3 | 380 | 28.00 |