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Statistical Quality Control for Human-Based Electronic Services

Robert Kern, Hans Thies & Gerhard Satzger

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abstract 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.
   
type conference paper (English)
   
keywords
   
name of conference 8th International Conference on Service-Oriented Computing (ICSOC) (San Francisco, USA)
date of conference 7-12-2010
title of proceedings Service-Oriented Computing
page(s) 243-257
publisher Springer (Heidelberg)
ISSN 978-3-642-17357-8
DOI 10.1007/978-3-642-17358-5_17
review not reviewed
   
citation Kern, R., Thies, H., & Satzger, G. (2010). Statistical Quality Control for Human-Based Electronic Services. In Service-Oriented Computing, pp.243-257. Heidelberg: Springer, DOI:10.1007/978-3-642-17358-5_17.