Natural Language Processing for Human Resources: A Survey
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866912291997351936 |
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| author | Otani, Naoki Bhutani, Nikita Hruschka, Estevam |
| author_facet | Otani, Naoki Bhutani, Nikita Hruschka, Estevam |
| contents | Advances in Natural Language Processing (NLP) have the potential to transform HR processes, from recruitment to employee management. While recent breakthroughs in NLP have generated significant interest in its industrial applications, a comprehensive overview of how NLP can be applied across HR activities is still lacking. This paper discovers opportunities for researchers and practitioners to harness NLP's transformative potential in this domain. We analyze key fundamental tasks such as information extraction and text classification, and their roles in downstream applications like recommendation and language generation, while also discussing ethical concerns. Additionally, we identify gaps in current research and encourage future work to explore holistic approaches for achieving broader objectives in this field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_16498 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Natural Language Processing for Human Resources: A Survey Otani, Naoki Bhutani, Nikita Hruschka, Estevam Computation and Language Advances in Natural Language Processing (NLP) have the potential to transform HR processes, from recruitment to employee management. While recent breakthroughs in NLP have generated significant interest in its industrial applications, a comprehensive overview of how NLP can be applied across HR activities is still lacking. This paper discovers opportunities for researchers and practitioners to harness NLP's transformative potential in this domain. We analyze key fundamental tasks such as information extraction and text classification, and their roles in downstream applications like recommendation and language generation, while also discussing ethical concerns. Additionally, we identify gaps in current research and encourage future work to explore holistic approaches for achieving broader objectives in this field. |
| title | Natural Language Processing for Human Resources: A Survey |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2410.16498 |