On the use of summarization and transformer architectures for profiling résumés
作者：
Highlights：
• Methodology to automatically profile résumés of job candidates.
• Text summarization of résumés improves performance.
• Transformer Architectures for representing résumés as real vectors.
• Profiles generated by applying hierarchical clustering to résumé embeddings.
• Profile hierarchies useful to satisfy job offers.
摘要
•Methodology to automatically profile résumés of job candidates.•Text summarization of résumés improves performance.•Transformer Architectures for representing résumés as real vectors.•Profiles generated by applying hierarchical clustering to résumé embeddings.•Profile hierarchies useful to satisfy job offers.
论文关键词：Profiling,Industry 4.0,Transformer,Summarization,Deep learning,Clustering
论文评审过程：Received 21 May 2020, Revised 28 June 2021, Accepted 29 June 2021, Available online 3 July 2021, Version of Record 12 July 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115521
