Research development on granular computing theory and method for big data

Jiye LIANG; Yuhua QIAN; Deyu Li; Qinghua HU

doi:10.11959/j.issn.2096-0271.2016038

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Research development on granular computing theory and method for big data

STUDY | 更新时间：2024-06-03

- Research development on granular computing theory and method for big data
- Big Data Research Vol. 2, Issue 4, Pages: 2016038(2016)
- 作者机构：
  
  1. 山西大学计算智能与中文信息处理教育部重点实验室，山西太原 030006
  2. 山西大学计算机与信息技术学院，山西太原 030006
  3. 天津大学计算机科学与技术学院，天津 300072
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2016038
  CLC： TP391
- Online First：2016-07，
  
  Published：20 July 2016
- 稿件说明：
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Jiye LIANG, Yuhua QIAN, Deyu Li, et al. Research development on granular computing theory and method for big data[J]. Big Data Research2016, 2(4): 2016038.
DOI：

Jiye LIANG, Yuhua QIAN, Deyu Li, et al. Research development on granular computing theory and method for big data[J]. Big Data Research2016, 2(4): 2016038. DOI： 10.11959/j.issn.2096-0271.2016038.

摘要

大数据的规模性、多模态性与增长性给传统的数据挖掘方法带来了挑战。粒计算作为智能信息处理领域中大规模复杂问题求解的有效方法，探索大数据分析的粒计算理论与方法有望为应对这些挑战提供新的思路和策略。瞄准若干大数据挖掘任务，对数据粒化、多粒度模式发现与融合、多粒度/跨粒度推理等方面取得的一些进展进行梳理和剖析，并针对天文数据挖掘和微博数据挖掘两个典型示范应用领域的初步研究进行了总结，以期为大数据挖掘领域的研究做出有益的探索。

Abstract

Aiming at several data mining tasks

research developments on data granulation

multi-granularity pattern discovery and fusion

multi-granularity reasoning were carded and analyzed

and the preliminary study on two typical applications astronomical data mining and microblog data mining was summarized

which would be helpful for making a beneficial exploration in big data mining area.

关键词

Keywords

references

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