Recommendation System: A New Approach to Recommend Potential Profile Using AHP Method

Safia Baali
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Abstract

The most challenging problem in human resources specially in the IT digital services company, is to assign the best collaborator’s in the adequate project , then ensure the delivery’s performance.in this paper we aim to develop à recommandation System using based-content and collaborative filtering in order to recommend potential profiles for a new job offer. The Principal parts of this recommandation is the matching between job offer of new project and collaborators profiles and the scoring using AHP method. In the first step we propose a model of criteria to measure collective skills , we validate by a survey realized in the IT service company , we analyze the data collected using PCA method (Principal Component Analysis).the results indicate six factors to measure collective skills of each collaborator (Technical skill, Proactivity ,Integrity, Cooperation, Communication and Benevolence/Interpersonal Relationship), these factors are used in AHP function to give score for each collaborator then allow the recommendation for the adequate project.
推荐系统:一种基于AHP方法的潜在剖面推荐新方法
人力资源中最具挑战性的问题,特别是在IT数字服务公司,是在适当的项目中分配最佳的合作者,然后确保交付的性能。在本文中,我们的目标是开发一个基于内容和协同过滤的推荐系统,以便为新的工作机会推荐潜在的个人资料。该建议的主要部分是新项目的工作机会与合作者的个人资料之间的匹配,并使用AHP方法进行评分。在第一步中,我们提出了一个衡量集体技能的标准模型,我们通过在IT服务公司中实现的调查来验证,我们使用主成分分析(PCA)方法分析收集的数据。结果表明,衡量每个合作者的集体技能的六个因素(技术技能,主动性,完整性,合作,沟通和仁慈/人际关系),这些因素在AHP函数中被用来给每个合作者打分,然后允许推荐合适的项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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