Crowdsourcing in form of human-based electronic services (people services) provides a powerful way of outsourcing tasks to a large crowd of remote workers over the Internet. Research has shown that multiple redundant results delivered by different workers can be aggregated in order to achieve a reliable result. However, existing implementations of this approach are rather inefficient as they multiply the effort for task execution and are not able to guarantee a certain quality level. As a starting point towards an integrated approach for quality management of people services we have developed a quality management model that combines elements of statistical quality control (SQC) with group decision theory. The contributions of the workers are tracked and weighted individually in order to minimize the quality management effort while guaranteing a well-defined level of overall result quality. A quantitative analysis of the approach based on an optical character recognition (OCR) scenario confirms the efficiency and reach of the approach.
Language
English
HSG Classification
contribution to scientific community
Refereed
No
Book title
Service-Oriented Computing
Publisher
Springer
Publisher place
Heidelberg
Start page
243
End page
257
Pages
15
Event Title
8th International Conference on Service-Oriented Computing (ICSOC 2010)