Name
Abstract | ||
|---|---|---|
With the proliferation of mobile devices, mobile crowd sensing (MCS) has emerged as a new data collection paradigm, which allows the crowd to act as sensors and contribute their observations about entities. Unfortunately, users with varied skills and motivations may provide conflicting information for the same entity. Existing work solves this problem by estimating user reliability and inferring t... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TII.2019.2896287 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Sensors,Task analysis,Reliability,Monitoring,Navigation,Roads,Informatics | Sensing system,Computer science,Real-time computing,Artificial intelligence,Biclustering,Machine learning,Bayesian probability | Journal |
Volume | Issue | ISSN |
16 | 2 | 1551-3203 |
Citations | PageRank | References |
4 | 0.40 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Du | 1 | 14 | 6.47 |
| Yu-e Sun | 2 | 33 | 7.07 |
| He Huang | 3 | 829 | 65.14 |
| Liusheng Huang | 4 | 473 | 64.55 |
| Hongli Xu | 5 | 502 | 85.92 |
| Yu Bao | 6 | 35 | 6.69 |
| Hansong Guo | 7 | 14 | 3.39 |