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A hybrid approach to managing job offers and candidates

机译:管理工作机会和候选人的混合方法

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摘要

The evolution of the job market has resulted in traditional methods of recruitment becoming insufficient. As it is now necessary to handle volumes of information (mostly in the form of free text) that are impossible to process manually, an analysis and assisted categorization are essential to address this issue. In this paper, we present a combination of the E-Gen and cortex systems. E-Gen aims to perform analysis and categorization of job offers together with the responses given by the candidates. E-Gen system strategy is based on vectorial and probabilistic models to solve the problem of profiling applications according to a specific job offer, cortex is a statistical automatic summarization system. In this work, E-Gen uses Cortex as a powerful filter to eliminate irrelevant information contained in candidate answers. Our main objective is to develop a system to assist a recruitment consultant and the results obtained by the proposed combination surpass those of E-Gen in standalone mode on this task.
机译:就业市场的发展导致传统的招聘方法变得不足。由于现在有必要处理无法手动处理的信息量(大部分为自由文本形式),因此分析和辅助分类对于解决此问题至关重要。在本文中,我们介绍了E-Gen和皮质系统的组合。 E-Gen旨在对工作机会进行分析和分类,并提供候选人的反馈。 E-Gen系统策略基于矢量和概率模型,可根据特定工作机会解决应用程序分析问题,cortex是一种统计自动摘要系统。在这项工作中,E-Gen使用Cortex作为强大的过滤器,以消除候选答案中包含的不相关信息。我们的主要目标是开发一个系统来协助招聘顾问,并且通过提议的合并获得的结果在此任务上超过了E-Gen的独立模式。

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