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首页> 外文会议>Intelligent Agents, 2009. IA '09 >A fuzzy based agent for group decision support of applicants ranking within recruitment systems
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A fuzzy based agent for group decision support of applicants ranking within recruitment systems

机译：基于模糊的代理，为求职系统中排名的申请人提供群体决策支持

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摘要

An effective applicant selection procedure for job roles is one of the most significant requirements for organisations human resources (HR) departments. Due to the high number of applicants it is necessary to short-list and rank submitted CVs based on their suitability for the job requirements. To reduce costs, error and time there is a strong desire from companies towards automating the two processes of: specifying the requirements criteria for a given job (experience, skills, etc) and matching between the applicants' profiles and the job requirements; to produce an applicants' ranking policy that gives consistent and fair results which can be legally justified. However both these processes involve a high level of uncertainty, as they require the input of different occupation domain experts in the decision making process. These experts will have different opinions, expectations and interpretations for the requirements specification as well as for the applicants matching and ranking criteria. Determining the consistency and reliability of each expert's decision making behaviours is also necessary to ensure that experts decisions are unbiased and correctly weighted according to their level knowledge and experience. This paper presents a novel approach for ranking job applicants by employing fuzzy agents for handling the uncertainties and inconsistencies in group decisions of a panel of experts. The presented system will enable automating the processes of requirements specification and applicant's matching/ranking. Experiments have been performed within the residential care sector in which the proposed system has been shown to produce ranking decisions that were relatively highly consistent with those of the human experts.
机译：有效的求职者选拔程序是组织人力资源（HR）部门最重要的要求之一。由于申请人数量众多，有必要根据其对工作要求的适合程度对提交的简历进行筛选和排名。为了降低成本，减少错误和时间，公司强烈希望实现以下两个过程的自动化：指定给定工作的要求标准（经验，技能等）以及申请人的个人资料和工作要求之间的匹配；制定出申请人的排名政策，该政策会给出一致而公正的结果，这在法律上是合理的。但是，这两个过程都涉及高度的不确定性，因为它们需要决策过程中不同职业领域专家的输入。这些专家对于需求规范以及申请人的匹配和排名标准将有不同的意见，期望和解释。确定每位专家决策行为的一致性和可靠性对于确保专家决策不受偏见并根据其水平知识和经验正确权衡也是必要的。本文提出了一种新颖的方法，通过使用模糊代理来处理专家小组的集体决策中的不确定性和不一致性，从而对求职者进行排名。提出的系统将使需求说明和申请人的匹配/排名自动化。已在住宅护理部门内进行了实验，在该实验中，所建议的系统已显示出与人类专家的决策相对高度一致的排名决策。

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