Name
Title | ||
|---|---|---|
Inductive Gaussian representation of user-specific information for personalized stress-level prediction |
Abstract | ||
|---|---|---|
•Formulate a unified end-to-end model (PSP-IGR) for personalized stress-level prediction.•Categorize heterogeneous inputs into three categories according to their characteristics.•Devise Inductive Gaussian representation (IGR) for user-specific information.•Generalize to out-of-sample users under uncertainty modeling with IGR.•Evaluate effects of PSP-IGR and IGR on stress-level prediction accuracy. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.114912 | Expert Systems with Applications |
Keywords | DocType | Volume |
Context awareness,Knowledge representation,Neural networks,Personalization,Stress measurement,Inductive gaussian representation | Journal | 178 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Byungkook Oh | 1 | 0 | 0.34 |
| Jimin Hwang | 2 | 0 | 0.34 |
| Seungmin Seo | 3 | 24 | 5.68 |
| Sejin Chun | 4 | 0 | 0.34 |
| Kyong-Ho Lee | 5 | 439 | 47.52 |