Evaluation of High-Recall Human-in-the-Loop Information Retrieval Technologies

高召回率人在环信息检索技术的评估

• 批准号: RGPIN-2017-04239
• 负责人: Grossman, Maura
• 金额: $ 1.46万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634972
• 关键词: Evaluation; Recall; Human; Loop; Information

The objective of high-recall information retrieval (HRIR) is to identify substantially all information relevant to an information need, where the consequences of missing or untimely results may have serious legal, policy, health, social, safety, defence, or financial implications. To find acceptance in practice, HRIR technologies must be more effective—and must be shown to be more effective—than current practice, according to the legal, statutory, regulatory, ethical, or professional standards governing the application domain. The applicant is the leading expert in this field, having first recognized the transferability of machine-learning technologies from spam filtering to electronic discovery, and then having established the scientific foundation for their acceptance in civil litigation and regulatory proceedings, both in the United States and Europe.

高查全率信息检索（HRIR）的目标是识别与信息需求相关的基本所有信息，其中缺失或不及时的结果可能会产生严重的法律的、政策、健康、社会、安全、国防或财务影响。 为了在实践中获得认可，HRIR技术必须比当前的实践更有效，并且必须根据管理应用领域的法律的、法规、规章、道德或专业标准来证明HRIR技术更有效。 申请人是这一领域的领先专家，首先认识到机器学习技术从垃圾邮件过滤到电子发现的可转移性，然后为美国和欧洲的民事诉讼和监管程序接受这些技术奠定了科学基础。