Name
Abstract | ||
|---|---|---|
Although online social networks reflect real world social relationships, in many cases, online data is too scarce or implicit to reveal a user's true willingness. This causes the Blind Spot problem in socially-rendered willingness inference systems. Blind spots are the undervalued online contacts in willingness inference because of insufficient explicit evidences. To the best of our knowledge, this is the first time to introduce and address the blind spot problem. In this paper, we propose a scheme to detect blind spots, by contradicting explicit evidences and implicit inferences. The proposed scheme uses interaction history as the explicit evidence, and social circles for implicit inference. Real world experiments and surveys demonstrate that our scheme can detect blind spots. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/GLOCOM.2012.6503420 | GLOBECOM |
Keywords | Field | DocType |
socially-rendered willingness inference system,user true willingness,user interfaces,inference mechanisms,blind spot problem,social relationship,online social network,implicit inference,explicit evidence,social networking (online),online contact | Interaction history,Data science,Internet privacy,Social relationship,Social network,Computer science,Inference,Computer network,Blind spot | Conference |
ISSN | ISBN | Citations |
1930-529X E-ISBN : 978-1-4673-0919-6 | 978-1-4673-0919-6 | 2 |
PageRank | References | Authors |
0.37 | 17 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Di Wang | 1 | 1337 | 143.48 |
| Xinxin Liu | 2 | 151 | 8.79 |
| Xiaolin Li | 3 | 405 | 37.36 |