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SYSTEMS AND METHODS TO IDENTIFY RESUMES BASED ON STAGED MACHINE LEARNING MODELS

机译:基于分段机器学习模型的简历识别系统和方法

摘要

Systems, methods, and non-transitory computer readable media are configured to generate a relevance score for each resume of a plurality of resumes associated with job candidates based on one or more machine learning models in a first stage associated with a job pipeline of an organization, the relevance score indicative of relevance of the resume in relation to the job pipeline. A subset of resumes are selected from the plurality of resumes, the subset of resumes having highest relevance scores. A quality score for each selected resume of the subset of resumes is generated based on a machine learning model in a second stage associated with the job pipeline, the quality score indicative of quality of the selected resume in relation to the job pipeline.
机译:系统,方法和非暂时性计算机可读介质被配置为基于与组织的工作流水线相关联的第一阶段中的一个或多个机器学习模型为与求职者相关联的多个简历中的每个简历生成相关性得分。 ,是表示简历与工作管道相关性的相关性得分。从多个履历中选择履历的子集,该履历的子集具有最高的相关性得分。基于与作业流水线相关联的第二阶段中的机器学习模型,生成简历子集的每个所选简历的质量得分,该质量得分指示相对于作业流水线的所选简历的质量。

著录项

  • 公开/公告号US2018130024A1

    专利类型

  • 公开/公告日2018-05-10

    原文格式PDF

  • 申请/专利权人 FACEBOOK INC.;

    申请/专利号US201615346162

  • 发明设计人 MIAOQING FANG;JESSE WILLIAM CZELUSTA;

    申请日2016-11-08

  • 分类号G06Q10/10;G06N99;

  • 国家 US

  • 入库时间 2022-08-21 13:00:32

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