Name
Abstract | ||
|---|---|---|
We hypothesize that behavioral patterns of people are reflected in how they interact with their mobile devices and that continuous sensor data passively collected from their phones and wearables can infer their job performance. Specifically, we study day-today job performance (improvement, no change, decline) of N=298 information workers using mobile sensing data and offer data-driven insights int... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MPRV.2021.3118570 | IEEE Pervasive Computing |
Keywords | DocType | Volume |
Predictive models,Sensors,Training,Standards,Performance evaluation,Feature extraction,Analytical models | Journal | 20 |
Issue | ISSN | Citations |
4 | 1536-1268 | 0 |
PageRank | References | Authors |
0.34 | 0 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shayan Mirjafari | 1 | 0 | 0.34 |
| Hessam Bagherinezhad | 2 | 0 | 0.34 |
| Subigya Nepal | 3 | 11 | 3.18 |
| Gonzalo J. Martinez | 4 | 0 | 1.01 |
| Koustuv Saha | 5 | 19 | 5.10 |
| Mikio Obuchi | 6 | 11 | 2.94 |
| Pino G. Audia | 7 | 6 | 0.80 |
| Nitesh V. Chawla | 8 | 5 | 1.10 |
| Anind Dey | 9 | 11484 | 959.91 |
| Aaron Striegel | 10 | 321 | 42.30 |
| Andrew T. Campbell | 11 | 0 | 0.34 |