Name
Abstract | ||
|---|---|---|
This paper presents a pioneering context-aware approach for quality of experience (QoE) measurement and prediction. The proposed approach incorporates an intuitive context-aware framework and decision theory. It is capable of incorporating several QoE related classes and context information to correctly measure and predict the overall QoE on a single scale. Our approach can be used in measuring and predicting QoE in both lab and living-lab settings based on user, device and network related context parameters. The predicted QoE can be beneficial for network operators to minimize network churn and can help application developers to build smart user-centric applications. We perform extensive experimentation and the results validate our approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICME.2011.6012098 | Multimedia and Expo |
Keywords | Field | DocType |
application developer,network churn,overall qoe,context information,intuitive context-aware framework,network operator,context parameter,decision-theoretic approach,pioneering context-aware approach,quality-of-experience measurement,qoe related class,prediction algorithms,quality of service,application development,bayesian methods,decision theory,codecs,ubiquitous computing,bayesian network | Data mining,Computer science,Quality of service,Context awareness,Bayesian network,Decision theory,Quality of experience,Ubiquitous computing,Codec,Bayesian probability | Conference |
ISSN | ISBN | Citations |
1945-7871 E-ISBN : 978-1-61284-349-0 | 978-1-61284-349-0 | 8 |
PageRank | References | Authors |
0.60 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karan Mitra | 1 | 169 | 17.84 |
| Christer Ahlund | 2 | 53 | 6.74 |
| Arkady Zaslavsky | 3 | 1133 | 81.03 |