面向大数据的粒计算理论与方法研究进展

Research development on granular computing theory and method for big data

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。

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.