Big Data analytics supported by AI algorithms can support skills localization and retrieval in the context of a labor market intelligence problem. We formulate and solve this problem through specific DataOps models, blending data sources from administrative and technical partners in several countries into cooperation, creating shared knowledge to support policy and decision-making. We then focus on the critical task of skills extraction from resumes and vacancies featuring state-of-the-art machine learning models. We showcase preliminary results with applied machine learning on real data from the employment agencies of the Netherlands and the Flemish region in Belgium. The final goal is to match these skills to standard ontologies of skills, jobs and occupations.
翻译:由AI 算法支持的大数据分析方法可以支持在劳动力市场情报问题背景下的技能本地化和检索。我们通过具体的DataOps模型制定和解决这一问题,将几个国家的行政和技术伙伴的数据来源纳入合作,创造共同的知识以支持政策和决策。然后,我们着重从简历和空缺中提取技能的重要任务,以最先进的机器学习模式为特点。我们通过应用机器学习荷兰和比利时佛兰德地区就业机构提供的真实数据来展示初步结果。最终目标是将这些技能与技能、工作和职业的标准模式相匹配。