计算机科学与探索 ›› 2015, Vol. 9 ›› Issue (6): 641-659.DOI: 10.3778/j.issn.1673-9418.1502013

• 综述·探索 • 上一篇    下一篇

海量数据挖掘过程相关技术研究进展

米允龙1,2,米春桥1,2+,刘文奇3   

  1. 1. 怀化学院 计算机工程系,湖南 怀化 418000
    2. 武陵山片区生态农业智能控制技术湖南省重点实验室,湖南 怀化 418000
    3. 昆明理工大学 理学院,昆明 650500
  • 出版日期:2015-06-01 发布日期:2015-06-04

Research Advance on Related Technology of Massive Data Mining Process

MI Yunlong1,2, MI Chunqiao1,2+, LIU Wenqi3   

  1. 1. Department of Computer Science, Huaihua University, Huaihua, Hunan 418000, China
    2. Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua, Hunan 418000, China
    3. Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China
  • Online:2015-06-01 Published:2015-06-04

摘要: 随着信息技术的发展,复杂、多样的海量数据给数据挖掘带来了新的挑战。为了更加深入全面地了解大数据环境下的数据挖掘技术的研究进展和应用,从海量数据挖掘过程的技术框架、算法、理论及模式方面进行了详细的阐述。概述了大数据的基本概念、处理流程及面临的问题,简述了数据挖掘的基本过程及相关算法,详细评述了海量数据挖掘过程的研究现状及面临的挑战,并从博弈论的角度、粒计算模型及大数据处理思维方面探讨了海量数据挖掘过程中的处理模式。

关键词: 海量数据, 数据挖掘, 博弈论, 粒计算, 认知计算

Abstract: With the development of information technology, the emergence of complex and diverse massive data has brought new challenges to data mining. This comprehensive overview is intended to elaborate the research advances and applications of big data mining from the following aspects: the general technology framework, algorithms, theories and patterns of massive data mining process. Firstly, this paper presents the basic concepts, general process procedures and problems of big data. Secondly, this paper sketches the basic processes of data mining and related algorithms. Thirdly, this paper discusses the details of present research situations and challenges in massive data mining process. Finally, this paper studies the processing patterns of massive data mining process from the perspectives of game theory, granular computing model and big data processing thinking.

Key words: massive data, data mining, game theory, granular computing, cognitive computing