Worker Competency Auto Calculation

Accurately estimating worker skills is a complex challenge that many organizations face. In this paper, we propose an innovative crowdsourcing algorithm based on mutual assessments, leveraging a customized PageRank algorithm to account for the expertise of evaluators. By implementing our method on real-world datasets from multiple organizations, we show that our algorithm provides highly accurate skill estimations. This approach offers a cost-effective and scalable solution for assessing workforce skills, optimizing team formation, and improving resource planning.

Key Points Covered:

• The crowdsourced mutual assessment method for skill estimation
• How the customized PageRank algorithm factors in the expertise of the assessor
• Experimental results demonstrating the effectiveness of the algorithm on 15 real-world datasets

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