论文标题
基于社区的数据集成课程和工作数据，以支持个性化职业教育建议
Community-Based Data Integration of Course and Job Data in Support of Personalized Career-Education Recommendations
论文作者
论文摘要
您的教育如何影响您的职业生涯？理想情况下，您参加的课程帮助您识别，雇用并执行您一直想要的工作。但是，并非所有课程都提供转移到现有工作和未来工作的技能；课程描述中使用的技能术语可能与招聘广告中列出的技能术语不同。在课程中教学的内容与工作所需的内容之间可能存在很大的技能差距。在这项研究中，我们提出了一种新颖的方法，通过利用异质数据集成和社区检测来整合广泛的课程描述和招聘广告数据。创新的异质图方法以及已确定的技能社区可以实现跨域信息建议，例如，鉴于教育概况，可以提供工作建议，并提供有关重新技能和提高技能的建议，以支持终身学习。
How does your education impact your professional career? Ideally, the courses you take help you identify, get hired for, and perform the job you always wanted. However, not all courses provide skills that transfer to existing and future jobs; skill terms used in course descriptions might be different from those listed in job advertisements; and there might exist a considerable skill gap between what is taught in courses and what is needed for a job. In this study, we propose a novel method to integrate extensive course description and job advertisement data by leveraging heterogeneous data integration and community detection. The innovative heterogeneous graph approach along with identified skill communities enables cross-domain information recommendation, e.g., given an educational profile, job recommendations can be provided together with suggestions on education opportunities for re- and upskilling in support of lifelong learning.
