人在回路的数据准备技术研究进展

范举; 陈跃国; 杜小勇

doi:10.11959/j.issn.2096-0271.2019046

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人在回路的数据准备技术研究进展

专题：大数据整理 | 更新时间：2024-06-03

- 人在回路的数据准备技术研究进展
- Progress on human-in-the-loop data preparation
- 大数据 2019年5卷第6期页码：2019046-1
- 作者机构：
  
  1. 中国人民大学数据工程与知识工程教育部重点实验室，北京 100872
  2. 中国人民大学信息学院，北京 100872
- 作者简介：
  
  [ "范举（1984- ），男，博士，中国人民大学数据工程与知识工程教育部重点实验室与信息学院副教授，中国计算机学会会员，数据库专业委员会委员。主要研究方向为数据库与大数据、众包数据管理、数据准备" ]
  [ "陈跃国（1978- ），男，博士，中国人民大学信息学院教授、博士生导师，中国计算机学会高级会员，数据库专业委员会委员，大数据专家委员会通信委员。主要研究方向为大数据分析系统和语义搜索" ]
  [ "杜小勇（1963- ），男，博士，中国人民大学信息学院教授、博士生导师，教育部数据工程与知识工程重点实验室主任，中国计算机学会会士，数据库专业委员会主任，《大数据》期刊编委会副主任，ACM Transactions on Data Science编委。主要研究方向为数据库与大数据、智能信息检索、知识工程" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61602488);国家自然科学基金资助项目;The National Natural Science Foundation of China(61632016);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1711261)
- DOI：10.11959/j.issn.2096-0271.2019046
  中图分类号： TP391
- 网络首发：2019-11，
  
  纸质出版：2019-11-15
- 稿件说明：
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范举, 陈跃国, 杜小勇. 人在回路的数据准备技术研究进展[J]. 大数据, 2019,5(6):2019046-1.

Ju FAN, Yueguo CHEN, Xiaoyong DU. Progress on human-in-the-loop data preparation[J]. Big Data Research, 2019, 5(6): 2019046-1.
范举, 陈跃国, 杜小勇. 人在回路的数据准备技术研究进展[J]. 大数据, 2019,5(6):2019046-1. DOI： 10.11959/j.issn.2096-0271.2019046.

Ju FAN, Yueguo CHEN, Xiaoyong DU. Progress on human-in-the-loop data preparation[J]. Big Data Research, 2019, 5(6): 2019046-1. DOI： 10.11959/j.issn.2096-0271.2019046.

摘要

随着数据分析技术的迅猛发展，数据准备越来越成为一个瓶颈性问题。以真实的数据分析场景为背景，分析了数据准备的两大核心挑战：人力成本高与时间周期长。在此基础上，介绍了人在回路数据准备技术的研究进展。交互式数据准备技术面向终端用户，通过与用户的交互预测其意图，并通过有效的预测算法来节省数据准备的时间。基于众包的数据准备技术引入互联网上的海量用户作为众包工人扩展计算能力，从而支持数据准备的基本任务，并研究如何对众包做质量控制与成本优化。最后，对人在回路的数据准备做出总结并探讨未来的挑战性问题。

Abstract

With the rapid development of data analytics

data preparation has become a major bottleneck.The two essential challenges for data preparation on cost and time were analyzed.To address the challenges

the research progress on human-in-theloop data preparation was reviewed.Firstly

interactive data preparation was reviewed

which aimed to reduce the time for data preparation by predictively interacting with the end users.Then

crowdsourced data preparation was introduced

which utilize human’s computational power from the crowd to support foundamental data preparation tasks

and developed algorithms for controlling result quality and reducing crowdsourcing cost.Finally

future research directions were summarized and discussed.

关键词

Keywords

references

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