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English(EN) Human Capital in Context: What Employment Survival Reveals About Worker-Firm Match

新AI模型量化雇员-企业匹配度以预测就业成功

研究人员开发了一种新颖的方法,通过分析雇佣关系的存活率来评估雇员-企业匹配的质量。该系统利用双塔神经网络将雇员和企业嵌入到共享空间中,匹配质量由它们各自向量的余弦相似度决定。该方法应用于包含1.01亿雇员和840万企业的数据库,表明匹配质量的提高显著降低了员工流失率,并带来了更高的员工收入、更快的企业增长、更高的盈利能力和更有价值的专利。 AI

影响 这项研究可能带来更高效的招聘流程和更好的人才配置,从而影响个人的职业轨迹和企业的整体生产力。

排序理由 学术论文,详细介绍了一个新模型及其在大数据集上的应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新AI模型量化雇员-企业匹配度以预测就业成功

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学术论文,详细介绍了一个新模型及其在大数据集上的应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jung Ho Choi, Mario Milone ·

    人力资本的背景:就业生存揭示了什么关于劳资匹配

    arXiv:2611.16058v1 Announce Type: cross Abstract: There is no best worker in general, only a best worker for a particular firm. We develop a measure of worker-firm match quality that treats fit as a property of the pair, learned from the survival of employment relationships. A tw…