Name
Abstract | ||
|---|---|---|
Inference of high-level context is becoming crucial in development of context-aware applications. An example is social context inference - i.e., deriving social relations based upon the user's daily communication with other people. The efficiency of this mechanism mainly depends on the method(s) used to draw inferences based on existing evidence and sample information, such as a training data. Our approach uses rule-based data mining, Bayesian network inference, and user feedback to compute the probabilities of another user being in the specific social relationship with a user whose daily communication is logged by a mobile phone. In addition, a privacy mechanism is required to ensure the user's personal integrity and privacy when sharing this user's sensitive context data. Therefore, the derived social relations are used to define a user's policies for context access control, which grant the restricted context information scope depending on the user's current context. Finally, we propose a distributed architecture capable of managing this context information based upon these context access policies. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/PERCOM.2009.4912890 | PerCom Workshops |
Keywords | Field | DocType |
context access control,social context inference,sensitive context data,high-level context,restricted context information scope,context information,social relationship,daily communication,policy management,current context,social relation,context access policy,knowledge based systems,sensors,distributed architecture,training data,bayesian methods,rule based,access control,authorisation,mobile computing,bayesian network,feedback,data integrity,probability,social context,computer networks,data privacy,mobile communication,data mining,feature extraction,telecommunications | Mobile computing,Data science,Internet privacy,Computer science,Inference,Knowledge-based systems,Context model,Data integrity,User modeling,Information privacy,Computer user satisfaction,Distributed computing | Conference |
ISSN | ISBN | Citations |
2474-2503 | temp-isbn | 8 |
PageRank | References | Authors |
0.64 | 11 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alisa Devlic | 1 | 95 | 9.46 |
| Roland Reichle | 2 | 235 | 15.57 |
| Michal Wagner | 3 | 8 | 0.64 |
| Manuele Kirsch Pinheiro | 4 | 23 | 2.41 |
| Yves Vanrompay | 5 | 83 | 10.94 |
| Yolande Berbers | 6 | 1195 | 93.02 |
| Massimo Valla | 7 | 154 | 14.19 |