SkillNER: Mining and mapping soft skills from any text

作者：

Highlights：

• A Text Mining Tool was developed to automatically extract soft skills from any sources.

• As an application of the results, a Cluster Analysis was performed on ESCO.

• We represent the relations among Job Profiles and among Soft Skills as Graphs.

• The Tool and the Graphs could bring multiple benefits to Firms, Institutions and Workers.

• The System is designed to be Cost-Effective and Easily Adaptable to other contexts.

摘要

•A Text Mining Tool was developed to automatically extract soft skills from any sources.•As an application of the results, a Cluster Analysis was performed on ESCO.•We represent the relations among Job Profiles and among Soft Skills as Graphs.•The Tool and the Graphs could bring multiple benefits to Firms, Institutions and Workers.•The System is designed to be Cost-Effective and Easily Adaptable to other contexts.

论文关键词：Soft Skill,Skill Analysis,Machine Learning,Text Mining,Named Entity Recognition

论文评审过程：Received 15 May 2020, Revised 18 June 2021, Accepted 30 June 2021, Available online 6 July 2021, Version of Record 9 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115544