河北大学学报(自然科学版) >

2018 , Vol. 38 >Issue 3: 299 - 308

DOI: https://doi.org/10.3969/j.issn.1000-1565.2018.03.011

大数据与大数据机器学习

  • 张素芳 ,
  • 翟俊海 ,
  • 王聪 ,
  • 沈矗 ,
  • 赵春玲
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张素芳(1966—),女,河北蠡县人,中国气象局气象干部培训学院河北分院副教授,主要从事机器学习方向研究. E-mail: mczsf@126.com

收稿日期: 2017-12-23

  网络出版日期: 2018-05-25

基金资助

国家自然科学基金资助项目(71371063);河北省自然科学基金资助项目(F2017201026);河北大学自然科学研究计划项目(799207217071);河北大学研究生创新资助项目(hbu2018ss47);河北大学大学生创新训练项目(2017071)

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Big data and big data machine learning

  • ZHANG Sufang ,
  • ZHAI Junhai ,
  • WANG Cong ,
  • SHEN Chu ,
  • ZHAO Chunling
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  • 1.Hebei Branch of China Meteorological Administration Training Centre, China Meteorological Administration, Baoding 071000, China; 2.Key Laboratory of Machine Learning and Computational Intelligence of Hebei Province, College of Mathematics and Information Science, Hebei University, Baoding 071002, China

Received date: 2017-12-23

  Online published: 2018-05-25

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本文引用格式

张素芳 , 翟俊海 , 王聪 , 沈矗 , 赵春玲 . 大数据与大数据机器学习[J]. 河北大学学报(自然科学版), 2018 , 38(3) : 299 -308 . DOI: 10.3969/j.issn.1000-1565.2018.03.011

Abstract

Big data era has arrived. The big data refers to the data which is usually characterized by the 5 features: volume, variety, velocity, veracity, and value. In recent years, big data research is the hottest research topic in the field of information processing, and has drawn great attention from industrial communities, academic communities and governments because big value can be found in big data. It is of great significance for companies or governments to make decisions using the knowledge found from big data. Big data introduces many challenges to traditional machine learning, which can be analyzed by the 5 features of- DOI:10.3969/j.issn.1000-1565.2018.03.011大数据与大数据机器学习张素芳1, 翟俊海2, 王聪2, 沈矗2, 赵春玲2(1.中国气象局气象干部培训学院河北分院,河北 保定 071000;2.河北省机器学习与计算智能重点实验室,河北大学 数学与信息科学学院,河北 保定 071002)摘 要 大数据时代已经到来,大数据是指具有海量(Volume)、多样(Variety)、时效(Velocity)、不精确(Veracity)和价值(Value)这5种特征的数据,大数据研究是近几年信息处理领域最热门的研究方向,已经引起了工业界、学术界乃至政府部门的高度关注.大数据之所以备受关注,是因为大数据里面蕴藏着巨大的价值.如何把蕴藏在大数据中的价值挖掘出来,为企业或政府部门提供决策支持具有重要的意义.大数据给传统的机器学习带来了许多挑战,这些挑战可以从大数据的5个特征或从5个不同的角度进行分析.本文首先介绍大数据的概念,并详细剖析大数据5种特征的内涵;然后在此基础上,重点分析大数据给机器学习带来的挑战及可能的解决方法.本文对从事大数据研究的人员,特别是从事大数据机器学习研究的人员具有较高的参考价值.关键词: 大数据;机器学习;云计算;决策支持中图分类号:TP181 文献标志码:A 【additional_page=336】文章编号:1000-1565(2018)03-0299-10Big data and big data machine learningZHANG Sufang1, ZHAI Junhai2, WANG Cong2, SHEN Chu2, ZHAO Chunling2(1.Hebei Branch of China Meteorological Administration Training Centre, China Meteorological Administration, Baoding 071000, China;2.Key Laboratory of Machine Learning and Computational Intelligence of Hebei Province, College of Mathematics and Information Science, Hebei University, Baoding 071002, China)Abstract: Big data era has arrived. The big data refers to the data which is usually characterized by the 5 features: volume, variety, velocity, veracity, and value. In recent years, big data research is the hottest research topic in the field of information processing, and has drawn great attention from industrial communities, academic communities and governments because big value can be found in big data. It is of great significance for companies or governments to make decisions using the knowledge found from big data. Big data introduces many challenges to traditional machine learning, which can be analyzed by the 5 features of- 收稿日期:2017-12-23 基金项目:国家自然科学基金资助项目(71371063);河北省自然科学基金资助项目(F2017201026);河北大学自然科学研究计划项目(799207217071);河北大学研究生创新资助项目(hbu2018ss47);河北大学大学生创新训练项目(2017071) 第一作者:张素芳(1966—),女,河北蠡县人,中国气象局气象干部培训学院河北分院副教授,主要从事机器学习方向研究.E-mail: mczsf@126.com 通信作者:翟俊海(1964—),男,河北易县人,河北大学教授,博士,主要从事机器学习和数据挖掘方向研究.E-mail:mczjh@126.com第3期张素芳等:大数据与大数据机器学习big data or from 5 different views.This paper firstly introduces the concept of big data,and carefully analyzes the connotations of the 5 features, and then mainly focuses on analyzing the challenges and the possible solutions. This paper can be very helpful to researchers in related fields, especially for the ones engaging in the study of big data machine learning.

Key words： big data; machine learning; cloud computing; decision making

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