| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 467031 | Applied Computing and Informatics | 2015 | 14 Pages |
Crowdsourcing has been widely accepted across a broad range of application areas. In crowdsourcing environments, the possibility of performing human computation is characterized with risks due to the openness of their web-based platforms where each crowd worker joins and participates in the process at any time, causing serious effect on the quality of its computation. In this paper, a combination of Trust-Based Access Control (TBAC) strategy and fuzzy-expert systems was used to enhance the quality of human computation in crowdsourcing environment. A TBAC-fuzzy algorithm was developed and implemented using MATLAB 7.6.0 to compute trust value (Tvalue), priority value as evaluated by fuzzy inference system (FIS) and finally generate access decision to each crowd-worker. In conclusion, the use of TBAC is feasible in improving quality of human computation in crowdsourcing environments.
