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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.16845437 |
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| _version_ | 1866901205163180032 |
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| author | IJSCAI |
| author_facet | IJSCAI |
| contents | <p>The job market has expanded exponentially in the past few years. With many recruiters and candidates, it<br>is not an easy task to match a perfect candidate with a perfect job. The recruiter targets candidates with<br>the required skill sets mentioned in the job descriptions, while candidates target their dream jobs. The<br>search frictions and skills mismatch are persistent problems. In this paper, we build a model that would<br>match companies with candidates with the right skills and workers with the right company. We have<br>further developed an algorithm to investigate people’s hiring history for better results.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16845437 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | JOB MATCHING USING ARTIFICIAL INTELLIGENCE IJSCAI <p>The job market has expanded exponentially in the past few years. With many recruiters and candidates, it<br>is not an easy task to match a perfect candidate with a perfect job. The recruiter targets candidates with<br>the required skill sets mentioned in the job descriptions, while candidates target their dream jobs. The<br>search frictions and skills mismatch are persistent problems. In this paper, we build a model that would<br>match companies with candidates with the right skills and workers with the right company. We have<br>further developed an algorithm to investigate people’s hiring history for better results.</p> |
| title | JOB MATCHING USING ARTIFICIAL INTELLIGENCE |
| url | https://doi.org/10.5281/zenodo.16845437 |