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A System for Stratified Sampling of Entity Resolution Results to Assess and Improve Accuracy with Minimal Clerical Review Effort

机译:实体解析结果的分层抽样系统,以最小的文书审查工作来评估和提高准确性

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摘要

Organizations across many industries from banking to medicine depend on master data that describe their customers, products and services. Data integration and unique representations of master data are supported by Entity Resolution processes to link records for the same master entity. Master data is key to the core operations of these organizations. Unfortunately, many of these organizations do not use a systematic method, or in some cases, use no method for measuring and improving the quality of record linkage provided by Entity Resolution. This research presents an implementation and proposed methodology for routinely and systematically measuring the quality of Entity Resolution results. The systematic measurement of quality is augmented with continued improvement through efficient clerical review methods for improving the quality of the Entity representations generated by Entity Resolution.
机译:从银行业到医药业,许多行业的组织都依赖于描述其客户,产品和服务的主数据。实体解析过程支持数据集成和主数据的唯一表示形式,以链接同一主实体的记录。主数据是这些组织核心运营的关键。不幸的是,这些组织中的许多组织没有使用系统的方法,或者在某些情况下,没有使用任何方法来衡量和改善实体解决方案提供的记录链接的质量。这项研究为例行和系统地测量实体分辨率结果的质量提供了一种实现方法和建议的方法。通过有效的文书审核方法来改进由实体解析生成的实体表示的质量,通过持续改进来增强质量的系统度量。

著录项

  • 作者

    Pullen, Daniel Lee.;

  • 作者单位

    University of Arkansas at Little Rock.;

  • 授予单位 University of Arkansas at Little Rock.;
  • 学科 Information science.;Computer science.;Information technology.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 205 p.
  • 总页数 205
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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