[1]吉根林,赵 斌.面向大数据的时空数据挖掘综述[J].南京师大学报(自然科学版),2014,37(01):1.
 Ji Genlin,Zhao Bin.A Survey of Spatiotemporal Data Mining for Big Data[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(01):1.
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面向大数据的时空数据挖掘综述()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
第37卷
期数:
2014年01期
页码:
1
栏目:
出版日期:
2014-03-30

文章信息/Info

Title:
A Survey of Spatiotemporal Data Mining for Big Data
作者:
吉根林赵 斌
南京师范大学计算机科学与技术学院,江苏 南京 210023
Author(s):
Ji GenlinZhao Bin
School of Computer Science and Technology,Nanjing Normal University,Nanjing 210023,China
关键词:
时空数据挖掘时空大数据时空模式发现时空聚类时空分类时空异常检测
Keywords:
spatiotemporal data miningspatiotemporal big dataspatiotemporal pattern miningspatiotemporal clusteringspatiotemporal classificationspatiotemporal outlier detection
分类号:
TP181
文献标志码:
A
摘要:
时空数据挖掘是数据挖掘领域的前沿研究课题,正致力于开发和应用新兴的计算技术来分析海量、高维的时空数据,揭示时空数据中的有价值知识.本文以时空大数据为背景,介绍数据挖掘技术产生的背景与发展、时空数据挖掘的研究现状、研究内容、应用领域、面向大数据的时空数据挖掘系统架构以及实现技术,为相关领域的研究者提供参考.
Abstract:
Spatiotemporal data mining has emerged as an active research field,focusing on the development of computing technologies for the extraction of useful information and knowledge from massive and complex spatiotemporal database.This paper mainly focuses on spatiotemporal data mining for big data,introduces the background and development of data mining,the recent theoretical and applied research progress in spatiotemporal data mining,and discusses the infrastructure and technologies of spatiotemporal data mining for big data.

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相似文献/References:

[1]吉根林,王 敏.时空轨迹聚集模式挖掘研究进展[J].南京师大学报(自然科学版),2015,38(04):1.
 Ji Genlin,Wang Min.Research Progress of Mining of Gathering Patternin Spatio-Temporal Trajectory[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(01):1.

备注/Memo

备注/Memo:
收稿日期:2013-08-10.
基金项目:国家自然科学基金(40871176).
通讯联系人:吉根林,博士,教授,博士生导师,研究方向:数据挖掘与云计算.E-mail:glji@njnu.edu.cn
更新日期/Last Update: 2014-03-30