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Issue 5(1), October 2010 -- Paper Abstracts
Girard  (p. 9-22)
Cooper (p. 23-32)
Kunz-Osborne (p. 33-41)
Coulmas-Law (p.42-46)
Stasio (p. 47-56)
Albert-Valette-Florence (p.57-63)
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JOURNAL OF ORGANIZATIONAL PSYCHOLOGY

Worker Skill Estimation from Crowdsourced Mutual Assessments


Author(s): Shuwei Qiang, Amrinder Arora

Citation: Shuwei Qiang, Amrinder Arora, (2017) "Worker Skill Estimation from Crowdsourced Mutual Assessments," Journal of Organizational Psychology, Vol. 17, Iss. 4 , pp. 10-18

Article Type: Research paper

Publisher: North American Business Press

Abstract:

Current approaches for estimating skill levels of workforce either do not take into account the expertise of the recommender, or require intricate and expensive processes. In this paper, we propose a crowdsourcing algorithm for worker skill estimation based on mutual assessments. We propose a customized version of PageRank algorithm wherein we specifically considered the expertise of the person who made assessments. By implementing our algorithm on 15 real-world datasets from organizations and companies of varying sizes and domains and by using leave-one-out cross validation, we find that the results are highly correlated with the ground truth in datasets.