Author
Etuk, A., Norman, T. J., Şensoy, Murat, Srivatsa, M.
Publication Date
2017
Publication Place
-
Springer International Publishing
Subject
Trust, Reputation, Diversity, Sampling
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
1387-2532
Record ID
d3bf7aa2-2858-4161-b817-b1a0c1700ea7
Library Location
Computer Science
Date
2017
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can affect decisions. Existing trust and reputation mechanisms typically rely on reports from as many sources as possible to mitigate the influence of misleading reports on decisions. In the real world, however, it is often the case that querying information sources can be costly in terms of energy, bandwidth, delay overheads, and other constraints. We present a model of source selection and fusion in resource-constrained environments, where there is uncertainty regarding the trustworthiness of sources. We exploit diversity among sources to stratify them into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases. Through controlled experiments, we demonstrate that a diversity-based approach is robust to biases introduced due to dependencies among source reports, performs significantly better than existing approaches when sampling budget is limited and equally as good with an unlimited budget.
DOI
10.1007/s10458-016-9337-5
Cilt
31
