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Abstract
This paper proposes a data-driven solution to assess job skill value from a market-oriented perspective. The task is formulated as a Salary-Skill Value Composition Problem, where job salary is influenced by the context-aware value of required skills. A cooperative neural network, Salary-Skill Composition Network (SSCN), is proposed to separate and measure skill value from job postings. Experiments show SSCN effectively assigns skill values and outperforms benchmark models for salary prediction.
Publisher
NATURE COMMUNICATIONS
Published On
Mar 31, 2021
Authors
Ying Sun, Fuzhen Zhuang, Hengshu Zhu, Qi Zhang, Qing He, Hui Xiong
Tags
job skill value
salary prediction
data-driven solution
context-aware
neural network
market-oriented perspective

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