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Scientific Information Research

Keywords

multi-layer vocational-skill network; cross-job descriptors; industrial talent demand; dynamic observing

Abstract

[Purpose/ signficance]As an important tool for labor market observation，the relative robustness and other characteristics inherent in the traditional occupational classification system make it difficult to reflect changes in industrial talent demand in a timely manner. To solve this problem，this paper focuses on how to use digital means to map the relationship between occupations and skill requirements，and how to construct a multi-layer vocation-skill network and how to realize it. [Method/process]Firstly，design a set of cross-job descriptors，a common language for describing different jobs in Chinese context，in order to establish a vocation description framework for recruitment data development and utilization. Secondly，the Key technology of occupational intelligence classification based on job description text is established，and then a set of methods and models for the construction of a multi-layer vocational skill network reflecting the gradual specialization of skill requirements are formed; Finally，the method is validated by taking Shanghai IC industry as an example. [Result/conclusion]The experimental results show that the multi-layered job-skill network，which originates from the actual employment activities of enterprises，can assist us in observing diverse industrial talent needs with multi-dimensional granularity and flexibility.

Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2024.04.005

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